14.1.6 Transfer Learning from Other Tasks, Other Classes

Yang, C.Y.[Chun-Yu], Zhou, J.[Jie],
Non-stationary data sequence classification using online class priors estimation,
PR(41), No. 8, August 2008, pp. 2656-2664.
Elsevier DOI 0805
Concept drift; Online classification; EM BibRef

Zhang, Z.H.[Zhi-Hao], Zhou, J.[Jie],
Transfer estimation of evolving class priors in data stream classification,
PR(43), No. 9, September 2010, pp. 3151-3161.
Elsevier DOI 1006
Concept drift; Transfer learning; Prior estimation BibRef

Gao, X.B.[Xin-Bo], Wang, X.M.[Xiu-Mei], Li, X.L.[Xue-Long], Tao, D.C.[Da-Cheng],
Transfer latent variable model based on divergence analysis,
PR(44), No. 10-11, October-November 2011, pp. 2358-2366.
Elsevier DOI 1101
Dimensionality reduction; Latent variable model; Transfer learning; Bregman divergence BibRef

Pang, J., Huang, Q., Yan, S., Jiang, S., Qin, L.,
Transferring Boosted Detectors Towards Viewpoint and Scene Adaptiveness,
IP(20), No. 5, May 2011, pp. 1388-1400.
IEEE DOI 1104
Training set isn't exactly the same as test data. BibRef

di Carlo, S., Falasconi, M., Sanchez, E., Scionti, A., Squillero, G., Tonda, A.,
Increasing pattern recognition accuracy for chemical sensing by evolutionary based drift compensation,
PRL(32), No. 13, 1 October 2011, pp. 1594-1603.
Elsevier DOI 1109
Sensor drift; Evolutionary strategy; Classification systems BibRef

Gonçalves, Jr., P.M.[Paulo Mauricio], Maior de Barros, R.S.[Roberto Souto],
RCD: A recurring concept drift framework,
PRL(34), No. 9, July 2013, pp. 1018-1025.
Elsevier DOI 1305
Data streams; Concept drift; Recurring contexts; On-line learning; Multivariate non-parametric statistical test BibRef

Salakhutdinov, R.[Ruslan], Tenenbaum, J.B.[Joshua B.], Torralba, A.B.[Antonio B.],
Learning with Hierarchical-Deep Models,
PAMI(35), No. 8, 2013, pp. 1958-1971.
IEEE DOI 1307
BibRef
Earlier: A1, A3, A2:
Learning to share visual appearance for multiclass object detection,
CVPR11(1481-1488).
IEEE DOI 1106
Bayesian methods; Deep networks. Rare objects "borrow" statistical info from related common objects. Learn hierarchy of objects. BibRef

Lin, D.[Di], An, X.[Xing], Zhang, J.[Jian],
Double-bootstrapping source data selection for instance-based transfer learning,
PRL(34), No. 11, 1 August 2013, pp. 1279-1285.
Elsevier DOI 1306
Transfer learning; Instance-based transfer learning; Source data selection; Bagging BibRef

Varga, R., Nedevschi, S.,
Label Transfer by Measuring Compactness,
IP(22), No. 12, 2013, pp. 4711-4723.
IEEE DOI 1312
feature extraction BibRef

Li, Q.[Qing], Chen, X.W.[Xiao-Wu], Song, Y.F.[Ya-Fei], Zhang, Y., Jin, X.[Xin], Zhao, Q.P.[Qin-Ping],
Geodesic Propagation for Semantic Labeling,
IP(23), No. 11, November 2014, pp. 4812-4825.
IEEE DOI 1410
BibRef
Earlier: A2, A1, A3, A5, A6, Only:
Supervised Geodesic Propagation for Semantic Label Transfer,
ECCV12(III: 553-565).
Springer DOI 1210
Image color analysis BibRef

Khamis, S.[Sameh], Lampert, C.H.[Christoph H.],
CoConut: Co-Classification with Output Space Regularization,
BMVC14(xx-yy).
HTML Version. 1410
Jointly classifying multiple, otherwise independent, data samples. BibRef

Fang, M.[Min], Guo, Y.[Yong], Zhang, X.S.[Xiao-Song], Li, X.[Xiao],
Multi-source transfer learning based on label shared subspace,
PRL(51), No. 1, 2015, pp. 101-106.
Elsevier DOI 1412
Transfer learning BibRef

Sun, C.[Chao], Bao, B.K.[Bing-Kun], Xu, C.S.[Chang-Sheng],
Knowing Verb From Object: Retagging With Transfer Learning on Verb-Object Concept Images,
MultMed(17), No. 10, October 2015, pp. 1747-1759.
IEEE DOI 1511
Bayes methods BibRef

Xu, Y., Fang, X., Wu, J., Li, X., Zhang, D.,
Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation,
IP(25), No. 2, February 2016, pp. 850-863.
IEEE DOI 1601
Adaptation models BibRef

Deng, C., Tang, X., Yan, J., Liu, W., Gao, X.,
Discriminative Dictionary Learning With Common Label Alignment for Cross-Modal Retrieval,
MultMed(18), No. 2, February 2016, pp. 208-218.
IEEE DOI 1601
Correlation BibRef

Mudunuri, S.P.[Sivaram Prasad], Biswas, S.[Soma],
A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching,
PRL(71), No. 1, 2016, pp. 38-44.
Elsevier DOI 1602
Face recognition BibRef

Mandal, D., Biswas, S.[Soma],
Generalized Coupled Dictionary Learning Approach With Applications to Cross-Modal Matching,
IP(25), No. 8, August 2016, pp. 3826-3837.
IEEE DOI 1608
Correlation BibRef

Das, N., Mandal, D., Biswas, S.[Soma],
Simultaneous Semi-Coupled Dictionary Learning for Matching in Canonical Space,
IP(26), No. 8, August 2017, pp. 3995-4004.
IEEE DOI 1707
BibRef
Earlier:
Simultaneous Semi-Coupled Dictionary Learning for Matching RGBD Data,
Biometrics16(243-251)
IEEE DOI 1612
image matching, image representation, Mahalanobis metric, canonical representation, canonical space, cross-modal recognition, simultaneous semicoupled dictionary learning, sparse coefficients, Couplings, Dictionaries, Linear programming, Measurement, Testing, Training, Cross-modal matching, RGBD data, audio-image data, privileged information, text-image, data BibRef

An, T.H.[Taeg-Hyun], Hong, K.S.[Ki-Sang],
Label transfer via sparse representation,
PRL(70), No. 1, 2016, pp. 1-7.
Elsevier DOI 1602
Scene parsing BibRef

Zhang, L.[Lei], Zuo, W.M.[Wang-Meng], Zhang, D.,
LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation,
IP(25), No. 3, March 2016, pp. 1177-1191.
IEEE DOI 1602
Big Data BibRef

Zhou, S.[Shuang], Smirnov, E.[Evgueni], Schoenmakers, G.[Gijs], Driessens, K.[Kurt], Peeters, R.[Ralf],
Testing exchangeability for transfer decision,
PRL(88), No. 1, 2017, pp. 64-71.
Elsevier DOI 1703
Instance-transfer learning BibRef

Qi, G.J., Liu, W., Aggarwal, C., Huang, T.,
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes,
PAMI(39), No. 7, July 2017, pp. 1360-1373.
IEEE DOI 1706
Bridges, Noise measurement, Semantics, Training, Transfer functions, Videos, Visualization, Multimodal analysis, image classification, intermodal and intramodal label transfers (I2LT), zero-shot, learning BibRef

Wang, J.[Jun], Wang, G.Q.[Guo-Qing], Li, L.[Leida],
Image Pattern Similarity Index and Its Application to Task-Specific Transfer Learning,
IEICE(E100-D), No. 12, December 2017, pp. 3032-3035.
WWW Link. 1712
BibRef

Gao, N.N.[Neng-Neng], Huang, S.J.[Sheng-Jun], Yan, Y.F.[Yi-Fan], Chen, S.C.[Song-Can],
Cross modal similarity learning with active queries,
PR(75), No. 1, 2018, pp. 214-222.
Elsevier DOI 1712
Active learning BibRef

Zhang, B.C.[Bao-Chang], Perina, A.[Alessandro], Li, C.[Ce], Ye, Q.X.[Qi-Xiang], Murino, V.[Vittorio], del Bue, A.[Alessio],
Manifold constraint transfer for visual structure-driven optimization,
PR(77), 2018, pp. 87-98.
Elsevier DOI 1802
Manifold, Transfer learning, Alternating direction method of multipliers, Object tracking, Object categorization BibRef

Kumar, S.[Suren], Dhiman, V.[Vikas], Koch, P.A.[Parker A.], Corso, J.J.[Jason J.],
Learning Compositional Sparse Bimodal Models,
PAMI(40), No. 5, May 2018, pp. 1032-1044.
IEEE DOI 1804
Transfer from, e.g., red triangles/blue squares to red squares/blue triangles. Dictionaries, Encoding, Poles and towers, Robot sensing systems, Semantics, Visualization, Multimodal learning, tabletop robotics BibRef

Zheng, F.[Feng], Tang, Y.[Yi], Shao, L.[Ling],
Hetero-Manifold Regularisation for Cross-Modal Hashing,
PAMI(40), No. 5, May 2018, pp. 1059-1071.
IEEE DOI 1804
Data models, Euclidean distance, Hamming distance, Manifolds, Semantics, Support vector machines, Training, Cross-modal hashing, manifold regularisation BibRef

Zhu, F.[Fan], Shao, L.[Ling], Tang, J.[Jun],
Boosted Cross-Domain Categorization,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Chang, H.[Hang], Han, J.[Ju], Zhong, C.[Cheng], Snijders, A.M.[Antoine M.], Mao, J.H.[Jian-Hua],
Unsupervised Transfer Learning via Multi-Scale Convolutional Sparse Coding for Biomedical Applications,
PAMI(40), No. 5, May 2018, pp. 1182-1194.
IEEE DOI 1804
Biological neural networks, Convolutional codes, Encoding, Feature extraction, Knowledge engineering, Training, sharable information BibRef

Peng, P.X.[Pei-Xi], Tian, Y.H.[Yong-Hong], Xiang, T.[Tao], Wang, Y.W.[Yao-Wei], Pontil, M.[Massimiliano], Huang, T.J.[Tie-Jun],
Joint Semantic and Latent Attribute Modelling for Cross-Class Transfer Learning,
PAMI(40), No. 7, July 2018, pp. 1625-1638.
IEEE DOI 1806
Adaptation models, Computational modeling, Data models, Dictionaries, Semantics, Training, Visualization, Attribute learning, zero-shot learning BibRef

Guo, X.[Xin], Wang, S.[Song], Tie, Y.[Yun], Qi, L.[Lin], Guan, L.[Ling],
Joint intermodal and intramodal correlation preservation for semi-paired learning,
PR(81), 2018, pp. 36-49.
Elsevier DOI 1806
Semi-paired learning, Canonical correlation analysis, Clustering BibRef

Shi, Q., Liu, X., Huang, X.,
An Active Relearning Framework for Remote Sensing Image Classification,
GeoRS(56), No. 6, June 2018, pp. 3468-3486.
IEEE DOI 1806
Adaptation models, Convergence, Feature extraction, Remote sensing, Spectral analysis, Training, Uncertainty, Active learning (AL), relearning BibRef

Han, W.[Wei], Feng, R.[Ruyi], Wang, L.Z.[Li-Zhe], Cheng, Y.F.[Ya-Fan],
A semi-supervised generative framework with deep learning features for high-resolution remote sensing image scene classification,
PandRS(145), 2018, pp. 23-43.
Elsevier DOI 1810
Scene classification, Deep learning, Self-label, High resolution remote sensing images BibRef

Ding, Z., Fu, Y.,
Dual Low-Rank Decompositions for Robust Cross-View Learning,
IP(28), No. 1, January 2019, pp. 194-204.
IEEE DOI 1810
Manifolds, Robustness, Feature extraction, Face, Task analysis, Data models, Sensors, Cross-view learning, low-rank modeling, graph embedding BibRef

Ma, Z.C.[Zhong-Chen], Chen, S.C.[Song-Can], Ma, D.[Di],
Heterogeneous multi-output classification by structured conditional risk minimization,
PRL(116), 2018, pp. 50-57.
Elsevier DOI 1812
Multi-output classification, Problem transformation, Output structures, Heterogeneity, Structured prediction BibRef

Duan, L.J.[Li-Juan], En, Q.[Qing], Qiao, Y.H.[Yuan-Hua], Cui, S.[Song], Qing, L.Y.[Lai-Yun],
Deep feature representation based on privileged knowledge transfer,
PRL(119), 2019, pp. 62-70.
Elsevier DOI 1902
Feature representation, Privileged knowledge transfer, Deep neural network, Multi-object retrieval BibRef

Shi, Q.[Qian], Zhang, Y.P.[Yi-Peng], Liu, X.P.[Xiao-Ping], Zhao, K.[Kefei],
Regularised transfer learning for hyperspectral image classification,
IET-CV(13), No. 2, March 2019, pp. 188-193.
DOI Link 1902
BibRef

Tang, X.Y.[Xin-Yao], Du, B.[Bo], Huang, J.Z.[Jian-Zhong], Wang, Z.[Zengmao], Zhang, L.F.[Le-Fei],
On combining active and transfer learning for medical data classification,
IET-CV(13), No. 2, March 2019, pp. 194-205.
DOI Link 1902
BibRef

Luo, Y.[Yong], Wen, Y.G.[Yong-Gang], Liu, T.L.[Tong-Liang], Tao, D.C.[Da-Cheng],
Transferring Knowledge Fragments for Learning Distance Metric from a Heterogeneous Domain,
PAMI(41), No. 4, April 2019, pp. 1013-1026.
IEEE DOI 1903
Measurement, Task analysis, Face, Visualization, Feature extraction, Training, Transfer learning, nonlinear BibRef

Deng, C.[Cheng], Xue, Y.M.[Yu-Meng], Liu, X.L.[Xiang-Long], Li, C.[Chao], Tao, D.C.[Da-Cheng],
Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model for Hyperspectral Image Classification,
GeoRS(57), No. 3, March 2019, pp. 1741-1754.
IEEE DOI 1903
feature extraction, geophysical image processing, image classification, learning (artificial intelligence), transfer learning (TL) BibRef

Ji, R.R.[Rong-Rong], Gao, Y.[Yue], Hong, R.C.[Ri-Chang], Liu, Q.[Qiong], Tao, D.C.[Da-Cheng], Li, X.L.[Xue-Long],
Spectral-Spatial Constraint Hyperspectral Image Classification,
GeoRS(52), No. 3, March 2014, pp. 1811-1824.
IEEE DOI 1403
hyperspectral imaging BibRef

Luo, F.[Fulin], Du, B.[Bo], Zhang, L.P.[Liang-Pei], Zhang, L.F.[Le-Fei], Tao, D.C.[Da-Cheng],
Feature Learning Using Spatial-Spectral Hypergraph Discriminant Analysis for Hyperspectral Image,
Cyber(49), No. 7, July 2019, pp. 2406-2419.
IEEE DOI 1905
Feature extraction, Laplace equations, Learning systems, Cybernetics, Hyperspectral imaging, Image reconstruction, spatial-spectral information BibRef

Ye, R.[Rui], Dai, Q.[Qun], Li, M.L.[Mei-Ling],
A hybrid transfer learning algorithm incorporating TrSVM with GASEN,
PR(92), 2019, pp. 192-202.
Elsevier DOI 1905
Transfer learning, Ensemble selection, Genetic Algorithm based Selective Ensemble algorithm (GASEN), Transfer Learning algorithm incorporating TrSVM with GASEN (TrGASVM) BibRef

Wang, C.[Chao], Tuo, H.Y.[Hong-Ya], Wang, J.X.[Jie-Xin], Qiao, L.F.[Ling-Feng],
Discriminative transfer learning via local and global structure preservation,
SIViP(13), No. 4, June 2019, pp. 753-760.
Springer DOI 1906
BibRef

Zhang, J.[Jing], Li, W.Q.[Wan-Qing], Ogunbona, P.[Philip], Xu, D.[Dong],
Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition: A Problem-Oriented Perspective,
Surveys(51), No. 1, February 2019, pp. Article No 7.
DOI Link 1906
Survey, Transfer Learning. BibRef

Xue, S.[Shan], Lu, J.[Jie], Zhang, G.Q.[Guang-Quan],
Cross-domain network representations,
PR(94), 2019, pp. 135-148.
Elsevier DOI 1906
Network representation, Transfer learning, Random walk, Information network, Unsupervised learning, Feature learning BibRef

Yu, X.[Xu], Jiang, F.[Feng], Du, J.W.[Jun-Wei], Gong, D.W.[Dun-Wei],
A cross-domain collaborative filtering algorithm with expanding user and item features via the latent factor space of auxiliary domains,
PR(94), 2019, pp. 96-109.
Elsevier DOI 1906
Cross-domain collaborative filtering, Feature expansion, Funk-SVD decomposition, Classification, Latent factor space BibRef

Rostami, M.[Mohammad], Kolouri, S.[Soheil], Eaton, E.[Eric], Kim, K.[Kyungnam],
Deep Transfer Learning for Few-Shot SAR Image Classification,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Hong, D., Yokoya, N., Chanussot, J., Zhu, X.X.,
CoSpace: Common Subspace Learning From Hyperspectral-Multispectral Correspondences,
GeoRS(57), No. 7, July 2019, pp. 4349-4359.
IEEE DOI 1907
Hyperspectral imaging, Optimization, Satellites, Earth, Manifolds, Common subspace learning (CoSpace), cross-modality learning, remote sensing BibRef

Chen, W., Hsu, T.H., Tsai, Y.H., Chen, M., Wang, Y.F.,
Transfer Neural Trees: Semi-Supervised Heterogeneous Domain Adaptation and Beyond,
IP(28), No. 9, Sep. 2019, pp. 4620-4633.
IEEE DOI 1908
image classification, learning (artificial intelligence), pattern classification, trees (mathematics), zero-shot learning BibRef

Tan, M.[Min], Yu, J.[Jun], Zhang, H.Y.[Hong-Yuan], Rui, Y.[Yong], Tao, D.C.[Da-Cheng],
Image Recognition by Predicted User Click Feature With Multidomain Multitask Transfer Deep Network,
IP(28), No. 12, December 2019, pp. 6047-6062.
IEEE DOI 1909
Image recognition, Task analysis, Visualization, Predictive models, Adaptation models, Correlation, Computational modeling, word embedding BibRef

Yan, C., Li, L., Zhang, C., Liu, B., Zhang, Y., Dai, Q.,
Cross-Modality Bridging and Knowledge Transferring for Image Understanding,
MultMed(21), No. 10, October 2019, pp. 2675-2685.
IEEE DOI 1910
feature extraction, image classification, image representation, learning (artificial intelligence), multimedia systems, knowledge transferring BibRef

Li, X.H.[Xu-Hong], Grandvalet, Y.[Yves], Davoine, F.[Franck],
A baseline regularization scheme for transfer learning with convolutional neural networks,
PR(98), 2020, pp. 107049.
Elsevier DOI 1911
Transfer learning, Regularization, Convolutional networks BibRef

Sanodiya, R.K.[Rakesh Kumar], Mathew, J.[Jimson],
A novel unsupervised Globality-Locality Preserving Projections in transfer learning,
IVC(90), 2019, pp. 103802.
Elsevier DOI 1912
Discriminant analysis, Transfer learning, Domain adaptation, Manifold, Classification, Unsupervised learning, Dimensionality reduction BibRef

Han, N., Wu, J., Fang, X., Xie, S., Zhan, S., Xie, K., Li, X.,
Latent Elastic-Net Transfer Learning,
IP(29), 2020, pp. 2820-2833.
IEEE DOI 2001
Transfer learning, elastic-net, source domain, target domain, machine learning BibRef

Pires de Lima, R.[Rafael], Marfurt, K.[Kurt],
Convolutional Neural Network for Remote-Sensing Scene Classification: Transfer Learning Analysis,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001
BibRef

Zhang, B., Yang, W., Wang, Z., Zhuo, L., Han, J., Zhen, X.,
The Structure Transfer Machine: Theory and Applications,
IP(29), 2020, pp. 2889-2902.
IEEE DOI 2002
Manifolds, Deep learning, Training, Probabilistic logic, Object tracking, Task analysis, Transfer learning, learning theory BibRef

Das, D., Lee, C.S.G.,
A Two-Stage Approach to Few-Shot Learning for Image Recognition,
IP(29), 2020, pp. 3336-3350.
IEEE DOI 2002
Transfer learning, convolutional neural network, few-shot learning, image classification BibRef

Gholenji, E.[Elahe], Tahmoresnezhad, J.[Jafar],
Joint local and statistical discriminant learning via feature alignment,
SIViP(14), No. 3, April 2020, pp. 609-616.
Springer DOI 2004
Machine learning applied to unseen items. Domain shift. BibRef

Peng, Z., Zhang, W., Han, N., Fang, X., Kang, P., Teng, L.,
Active Transfer Learning,
CirSysVideo(30), No. 4, April 2020, pp. 1022-1036.
IEEE DOI 2004
Task analysis, Kernel, Bicycles, Linear programming, Machine learning, Training, Optimization, Negative transfer, information diversity BibRef

Dong, R.M.[Run-Min], Li, C.[Cong], Fu, H.H.[Hao-Huan], Wang, J.[Jie], Li, W.J.[Wei-Jia], Yao, Y.[Yi], Gan, L.[Lin], Yu, L.[Le], Gong, P.[Peng],
Improving 3-m Resolution Land Cover Mapping through Efficient Learning from an Imperfect 10-m Resolution Map,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Liu, W., Qin, R.,
A MultiKernel Domain Adaptation Method for Unsupervised Transfer Learning on Cross-Source and Cross-Region Remote Sensing Data Classification,
GeoRS(58), No. 6, June 2020, pp. 4279-4289.
IEEE DOI 2005
Domain adaptation (DA), image classification, remote sensing, stable index, transfer learning (TL), unsupervised learning BibRef

Lu, Y.[Ying], Luo, L.K.[Ling-Kun], Huang, D.[Di], Wang, Y.H.[Yun-Hong], Chen, L.M.[Li-Ming],
Knowledge Transfer in Vision Recognition: A Survey,
Surveys(53), No. 2, April 2020, pp. xx-yy.
DOI Link 2007
vision recognition, transfer learning, Knowledge transfer, machine learning BibRef

Geng, J., Deng, X., Ma, X., Jiang, W.,
Transfer Learning for SAR Image Classification Via Deep Joint Distribution Adaptation Networks,
GeoRS(58), No. 8, August 2020, pp. 5377-5392.
IEEE DOI 2007
Radar polarimetry, Probability distribution, Synthetic aperture radar, Training, Task analysis, transfer learning BibRef

Zhou, J.H.[Jian-Hang], Zeng, S.N.[Shao-Ning], Zhang, B.[Bob],
Two-stage knowledge transfer framework for image classification,
PR(107), 2020, pp. 107529.
Elsevier DOI 2008
Image classification, Teacher-student model, Two-stage classification, Sparse representation BibRef

Tamaazousti, Y.[Youssef], Le Borgne, H.[Hervé], Hudelot, C.[Céline], Seddik, M.E.A.[Mohamed-El-Amine], Tamaazousti, M.[Mohamed],
Learning More Universal Representations for Transfer-Learning,
PAMI(42), No. 9, September 2020, pp. 2212-2224.
IEEE DOI 2008
Task analysis, Visualization, Measurement, Semantics, Additives, Veins, Training, Universal representations, universality evaluation, visual recognition BibRef

Peng, Z., Jia, Y., Hou, J.,
Non-Negative Transfer Learning With Consistent Inter-Domain Distribution,
SPLetters(27), 2020, pp. 1720-1724.
IEEE DOI 2010
Correlation, Optimization, Knowledge transfer, Task analysis, Learning systems, Signal processing algorithms, Kernel, negative transfer BibRef

Liu, W.F.[Wei-Feng], Li, J.F.[Jin-Feng], Liu, B.[Baodi], Guan, W.[Weili], Zhou, Y.C.[Yi-Cong], Xu, C.S.[Chang-Sheng],
Unified Cross-domain Classification via Geometric and Statistical Adaptations,
PR(110), 2021, pp. 107658.
Elsevier DOI 2011
Domain adaptation, Statistical adaptation, Maximum mean discrepancy (MMD), Geometric adaptation, Nyström method BibRef

Liu, Y.S.[Yi-Shu], Ding, L.W.[Li-Wang], Chen, C.H.[Cong-Hui], Liu, Y.B.[Ying-Bin],
Similarity-Based Unsupervised Deep Transfer Learning for Remote Sensing Image Retrieval,
GeoRS(58), No. 11, November 2020, pp. 7872-7889.
IEEE DOI 2011
Training, Feature extraction, Image retrieval, Remote sensing, Task analysis, Convolutional neural networks, Machine learning, weighted Wasserstein ordinal (WWO) loss BibRef

Zhuang, F.Z.[Fu-Zhen], Qi, Z.Y.[Zhi-Yuan], Duan, K.Y.[Ke-Yu], Xi, D.B.[Dong-Bo], Zhu, Y.C.[Yong-Chun], Zhu, H.S.[Heng-Shu], Xiong, H.[Hui], He, Q.[Qing],
A Comprehensive Survey on Transfer Learning,
PIEEE(109), No. 1, January 2021, pp. 43-76.
IEEE DOI 2012
Survey, Transfer Learning. Task analysis, Semisupervised learning, Data models, Covariance matrices, Machine learning, Adaptation models, Kernel, transfer learning BibRef

Meng, M.[Min], Lan, M.C.[Meng-Cheng], Yu, J.[Jun], Wu, J.G.[Ji-Gang],
Coupled Knowledge Transfer for Visual Data Recognition,
CirSysVideo(31), No. 5, 2021, pp. 1776-1789.
IEEE DOI 2105
BibRef

Lu, Y.[Yuwu], Wang, W.J.[Wen-Jing], Yuan, C.[Chun], Li, X.L.[Xue-Long], Lai, Z.H.[Zhi-Hui],
Manifold Transfer Learning via Discriminant Regression Analysis,
MultMed(23), 2021, pp. 2056-2070.
IEEE DOI 2107
Learning systems, Manifolds, Sparse matrices, Task analysis, Image classification, Convergence, Regression analysis, Manifold. BibRef

Azzam, M.[Mohamed], Wu, W.H.[Wen-Hao], Cao, W.M.[Wen-Ming], Wu, S.[Si], Wong, H.S.[Hau-San],
KTransGAN: Variational Inference-Based Knowledge Transfer for Unsupervised Conditional Generative Learning,
MultMed(23), 2021, pp. 3318-3331.
IEEE DOI 2109
Training, Data models, Generators, Adaptation models, Task analysis, image classification BibRef

Shan, X.X.[Xin-Xin], Lu, Y.[Yue], Li, Q.L.[Qing-Li], Wen, Y.[Ying],
Model-Based Transfer Learning and Sparse Coding for Partial Face Recognition,
CirSysVideo(31), No. 11, November 2021, pp. 4347-4356.
IEEE DOI 2112
Face recognition, Feature extraction, Probes, Encoding, Image reconstruction, Training, Videos, Partial face recognition, feature reconstruction BibRef

Yu, Z.X.[Zheng-Xu], Shen, D.[Dong], Jin, Z.M.[Zhong-Ming], Huang, J.Q.[Jian-Qiang], Cai, D.[Deng], Hua, X.S.[Xian-Sheng],
Progressive Transfer Learning,
IP(31), 2022, pp. 1340-1348.
IEEE DOI 2202
Task analysis, Transfer learning, Feature extraction, Training, Proposals, Data models, image classification BibRef

Sun, Q.[Qianru], Liu, Y.Y.[Yao-Yao], Chen, Z.Z.[Zhao-Zheng], Chua, T.S.[Tat-Seng], Schiele, B.[Bernt],
Meta-Transfer Learning Through Hard Tasks,
PAMI(44), No. 3, March 2022, pp. 1443-1456.
IEEE DOI 2202
Task analysis, Adaptation models, Training, Feature extraction, Training data, Data models, Measurement, Few-shot learning, image classification BibRef

Özkanoglu, M.A.[Mehmet Akif], Ozer, S.[Sedat],
InfraGAN: A GAN architecture to transfer visible images to infrared domain,
PRL(155), 2022, pp. 69-76.
Elsevier DOI 2203
Domain transfer, GANs, Infrared image generation BibRef

Saleh, N.[Neven], Wahed, M.A.[Manal Abdel], Salaheldin, A.M.[Ahmed M.],
Transfer learning-based platform for detecting multi-classification retinal disorders using optical coherence tomography images,
IJIST(32), No. 3, 2022, pp. 740-752.
DOI Link 2205
Inception V3 Net, optical coherence tomography, retinal disorders, SqueezeNet, transfer learning BibRef

Fang, B.[Bei], Liu, Y.[Yu], Zhang, H.[Haokui], He, J.[Juhou],
Hyperspectral Image Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer Learning,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Jing, Z.H.[Ze-Huan], Li, P.[Peng], Wu, B.[Bin], Yuan, S.[Shibo], Chen, Y.C.[Ying-Chao],
An Adaptive Focal Loss Function Based on Transfer Learning for Few-Shot Radar Signal Intra-Pulse Modulation Classification,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Cai, J.J.[Jing-Jing], Gan, F.M.[Feng-Ming], Cao, X.H.[Xiang-Hai], Liu, W.[Wei], Li, P.[Peng],
Radar Intra-Pulse Signal Modulation Classification with Contrastive Learning,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Cai, J.J.[Jing-Jing], Guo, Y.C.[Yi-Cheng], Cao, X.H.[Xiang-Hai],
Automatic Radar Intra-Pulse Signal Modulation Classification Using the Supervised Contrastive Learning,
RS(16), No. 18, 2024, pp. 3542.
DOI Link 2410
BibRef

Han, K.[Kai], Rebuffi, S.A.[Sylvestre-Alvise], Ehrhardt, S.[Sébastien], Vedaldi, A.[Andrea], Zisserman, A.[Andrew],
AutoNovel: Automatically Discovering and Learning Novel Visual Categories,
PAMI(44), No. 10, October 2022, pp. 6767-6781.
IEEE DOI 2209
BibRef
Earlier: A1, A4, A5, Only:
Learning to Discover Novel Visual Categories via Deep Transfer Clustering,
ICCV19(8400-8408)
IEEE DOI 2004
Task analysis, Ranking (statistics), Data models, Annotations, Benchmark testing, Visualization, Transfer learning, incremental learning. image classification, learning (artificial intelligence), object recognition, pattern clustering, known classes, Dogs BibRef

Mensink, T.[Thomas], Uijlings, J.[Jasper], Kuznetsova, A.[Alina], Gygli, M.[Michael], Ferrari, V.[Vittorio],
Factors of Influence for Transfer Learning Across Diverse Appearance Domains and Task Types,
PAMI(44), No. 12, December 2022, pp. 9298-9314.
IEEE DOI 2212
Task analysis, Transfer learning, Semantics, Image segmentation, Training, Object detection, Transfer learning, computer vision BibRef

Cao, Z.J.[Zhang-Jie], You, K.[Kaichao], Zhang, Z.Y.[Zi-Yang], Wang, J.M.[Jian-Min], Long, M.S.[Ming-Sheng],
From Big to Small: Adaptive Learning to Partial-Set Domains,
PAMI(45), No. 2, February 2023, pp. 1766-1780.
IEEE DOI 2301
Handheld computers, Task analysis, Adaptation models, Training, Transfer learning, Shape, Generative adversarial networks, theoretical analysis BibRef

Huang, W.[Wei], Shi, Y.L.[Yi-Lei], Xiong, Z.[Zhitong], Wang, Q.[Qi], Zhu, X.X.[Xiao Xiang],
Semi-supervised bidirectional alignment for Remote Sensing cross-domain scene classification,
PandRS(195), 2023, pp. 192-203.
Elsevier DOI 2301
Remote sensing, Semi-supervised domain adaptation, Cross-domain classification, Bidirectional sample-class alignment BibRef

Ren, C.X.[Chuan-Xian], Luo, Y.W.[You-Wei], Dai, D.Q.[Dao-Qing],
BuresNet: Conditional Bures Metric for Transferable Representation Learning,
PAMI(45), No. 4, April 2023, pp. 4198-4213.
IEEE DOI 2303
Measurement, Task analysis, Kernel, Transfer learning, Training, Estimation, Manifolds, Transfer learning, conditional shift, few-shot learning BibRef

Sun, Y.[Yuan], Wang, X.[Xu], Peng, D.Z.[De-Zhong], Ren, Z.W.[Zhen-Wen], Shen, X.B.[Xiao-Bo],
Hierarchical Hashing Learning for Image Set Classification,
IP(32), 2023, pp. 1732-1744.
IEEE DOI 2303
Semantics, Hash functions, Task analysis, Kernel, Binary codes, Probes, Transforms, Image set classification, hierarchical hashing, bidirectional semantic representation BibRef

Wang, X.M.[Xin-Ming], Wang, C.[Chao], Song, X.[Xuan], Kirby, L.[Levi], Wu, J.G.[Jian-Guo],
Regularized Multi-Output Gaussian Convolution Process with Domain Adaptation,
PAMI(45), No. 5, May 2023, pp. 6142-6156.
IEEE DOI 2304
Transfer learning, Modeling, Convolution, Adaptation models, Data models, Predictive models, Gaussian processes, domain adaptation BibRef

Gao, Y.M.[Yi-Miao], Yang, Y.H.[Yue-Han],
Transfer learning on stratified data: joint estimation transferred from strata,
PR(140), 2023, pp. 109535.
Elsevier DOI 2305
Transfer learning, Stratified data, Penalized regression, Semiparametric regression BibRef

Ramirez, P.Z.[Pierluigi Zama], Cardace, A.[Adriano], de Luigi, L.[Luca], Tonioni, A.[Alessio], Salti, S.[Samuele], di Stefano, L.[Luigi],
Learning Good Features to Transfer Across Tasks and Domains,
PAMI(45), No. 8, August 2023, pp. 9981-9995.
IEEE DOI 2307
Task analysis, Feature extraction, Training, Multitasking, Transfer learning, Semantic segmentation, Estimation, task transfer BibRef

Wang, W.[Wei], Gao, J.Y.[Jun-Yu], Yang, X.S.[Xiao-Shan], Xu, C.S.[Chang-Sheng],
Many Hands Make Light Work: Transferring Knowledge from Auxiliary Tasks for Video-Text Retrieval,
MultMed(25), 2023, pp. 2661-2674.
IEEE DOI 2307
Videos, Task analysis, Feature extraction, Semantics, Data models, Graph neural networks, Pipelines, Auxiliary tasks, video-text retrieval BibRef

Hattula, E.[Emilia], Zhu, L.[Lingli], Raninen, J.[Jere], Oksanen, J.[Juha], Hyyppä, J.[Juha],
Advantages of Using Transfer Learning Technology with a Quantative Measurement,
RS(15), No. 17, 2023, pp. 4278.
DOI Link 2310
BibRef

Ye, M.C.[Min-Chao], Wang, C.L.[Cheng-Long], Meng, Z.H.[Zhi-Hao], Xiong, F.C.[Feng-Chao], Qian, Y.T.[Yun-Tao],
Domain-invariant attention network for transfer learning between cross-scene hyperspectral images,
IET-CV(17), No. 7, 2023, pp. 739-749.
DOI Link 2310
hyperspectral imaging, pattern classification BibRef

Li, X.J.[Xing-Jian], Abuduweili, A.[Abulikemu], Shi, H.[Humphrey], Yang, P.K.[Peng-Kun], Dou, D.J.[De-Jing], Xiong, H.[Haoyi], Xu, C.Z.[Cheng-Zhong],
Semi-supervised transfer learning with hierarchical self-regularization,
PR(144), 2023, pp. 109831.
Elsevier DOI 2310
BibRef
Earlier: A2, A1, A3, A7, A5, Only:
Adaptive Consistency Regularization for Semi-Supervised Transfer Learning,
CVPR21(6919-6928)
IEEE DOI 2111
Semi-supervised learning, Transfer learning, Fine-tuning, Deep learning, Hierarchical consistency, Adaptive sample selection. Adaptation models, Codes, Supervised learning, Benchmark testing BibRef

Zhang, B.J.[Bing-Jie], Gao, B.[Baolu], Liang, S.Y.[Si-Yuan], Li, X.Y.[Xiao-Yang], Wang, H.[Hao],
A Classification Algorithm Based on Improved Meta Learning and Transfer Learning for Few-Shot Medical Images,
IET-IPR(17), No. 12, 2023, pp. 3589-3598.
DOI Link 2310
Domain generalization, Few-shot learning, Medical image classification, Meta learning, Transfer learning BibRef

Guo, K.[Kehua], Shen, C.C.[Chang-Chun], Hu, B.[Bin], Hu, M.[Min], Kui, X.Y.[Xiao-Yan],
RSNet: Relation Separation Network for Few-Shot Similar Class Recognition,
MultMed(25), 2023, pp. 3894-3904.
IEEE DOI 2310
BibRef

Du, X.T.[Xiang-Tong], Liu, Z.D.[Zhi-Dong], Feng, Z.[Zunlei], Deng, H.[Hai],
DataMap: Dataset transferability map for medical image classification,
PR(146), 2024, pp. 110044.
Elsevier DOI 2311
Transfer learning, Transferability, Gradient attribution BibRef

Xu, T.[Tuo], Han, B.[Bing], Li, J.[Jie], Du, Y.F.[Yue-Fan],
A locally weighted, correlated subdomain adaptive network employed to facilitate transfer learning,
IVC(141), 2024, pp. 104887.
Elsevier DOI 2402
Domain adaptation, Correlation subdomain adaptation, Maximum mean difference, Correlation transfer learning, Deep learning BibRef

Wang, Y.X.[Ya-Xing], Gonzalez-Garcia, A.[Abel], Wu, C.[Chenshen], Herranz, L.[Luis], Khan, F.S.[Fahad Shahbaz], Jui, S.L.[Shang-Ling], Yang, J.[Jian], van de Weijer, J.[Joost],
MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains,
IJCV(132), No. 2, February 2024, pp. 490-514.
Springer DOI 2402
BibRef

Dehkordi, R.H.[Ramin Heidarian], Candiani, G.[Gabriele], Nutini, F.[Francesco], Carotenuto, F.[Federico], Gioli, B.[Beniamino], Cesaraccio, C.[Carla], Boschetti, M.[Mirco],
Towards an Improved High-Throughput Phenotyping Approach: Utilizing MLRA and Dimensionality Reduction Techniques for Transferring Hyperspectral Proximal-Based Model to Airborne Images,
RS(16), No. 3, 2024, pp. 492.
DOI Link 2402
BibRef

Alfano, P.D.[Paolo Didier], Pastore, V.P.[Vito Paolo], Rosasco, L.[Lorenzo], Odone, F.[Francesca],
Top-tuning: A study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods,
IVC(142), 2024, pp. 104894.
Elsevier DOI 2402
Fast kernel methods, Training on a budget, Fast training, Transfer learning, Image classification BibRef

Hoppe, H.[Hauke], Dietrich, P.[Peter], Marzahn, P.[Philip], Weiß, T.[Thomas], Nitzsche, C.[Christian], Freiherr-von-Lukas, U.[Uwe], Wengerek, T.[Thomas], Borg, E.[Erik],
Transferability of Machine Learning Models for Crop Classification in Remote Sensing Imagery Using a New Test Methodology: A Study on Phenological, Temporal, and Spatial Influences,
RS(16), No. 9, 2024, pp. 1493.
DOI Link 2405
BibRef

Davila, A.[Ana], Colan, J.[Jacinto], Hasegawa, Y.[Yasuhisa],
Comparison of fine-tuning strategies for transfer learning in medical image classification,
IVC(146), 2024, pp. 105012.
Elsevier DOI 2405
Medical image analysis, Fine-tuning, Transfer learning, Convolutional neural network, Image classification BibRef

Han, H.G.[Hong-Gui], Li, M.M.[Meng-Meng], Yang, H.Y.[Hong-Yan], Wu, X.L.[Xiao-Long], Han, H.Y.[Hua-Yun],
Ensemble filter-transfer learning algorithm,
PR(154), 2024, pp. 110581.
Elsevier DOI 2406
Transfer learning, Knowledge filter algorithm, Ensemble transfer mechanism, Model prediction BibRef

Zhu, P.[Peng], Zhang, X.R.[Xiang-Rong], Han, X.[Xiao], Cheng, X.[Xina], Gu, J.[Jing], Chen, P.[Puhua], Jiao, L.C.[Li-Cheng],
Cross-Domain Classification Based on Frequency Component Adaptation for Remote Sensing Images,
RS(16), No. 12, 2024, pp. 2134.
DOI Link 2406
BibRef

Liu, J.C.[Ji-Chuan], Li, X.[Xiao], Dong, C.X.[Chun-Xi],
Unknown Sample Selection and Discriminative Classifier Learning for Generalized Category Discovery,
JVCIR(102), 2024, pp. 104203.
Elsevier DOI 2407
Generalized Category Discovery, Linear subspace, Neighborhood relevance score, Unknown Samples Selection, Uncertainty augmentation loss BibRef

Huang, X.C.[Xi-Chen], Lu, Z.Z.[Zheng-Zhi], Peng, B.[Bo],
Enhancing Transferability with Intra-Class Transformations and Inter-Class Nonlinear Fusion on SAR Images,
RS(16), No. 14, 2024, pp. 2539.
DOI Link 2408
BibRef

Li, S.K.[Shi-Kun], Xia, X.B.[Xiao-Bo], Deng, J.K.[Jian-Kang], Ge, S.M.[Shi-Ming], Liu, T.L.[Tong-Liang],
Transferring Annotator- and Instance-Dependent Transition Matrix for Learning From Crowds,
PAMI(46), No. 11, November 2024, pp. 7377-7391.
IEEE DOI 2410
Noise, Annotations, Noise measurement, Knowledge transfer, Data models, Sparse matrices, Estimation, Learning from crowds, knowledge transfer BibRef

Hadikhani, P.[Parham], Lai, D.T.C.[Daphne Teck Ching], Ong, W.H.[Wee-Hong], Nadimi-Shahraki, M.H.[Mohammad H.],
Automatic deep sparse clustering with a dynamic population-based evolutionary algorithm using reinforcement learning and transfer learning,
IVC(151), 2024, pp. 105258.
Elsevier DOI 2411
Unsupervised learning, Deep clustering, Reinforcement learning, Transfer learning, Evolutionary algorithm, Dimension reduction BibRef

Hong, Z.M.[Zi-Ming], Shen, L.[Li], Liu, T.L.[Tong-Liang],
Your Transferability Barrier is Fragile: Free-Lunch for Transferring the Non-Transferable Learning,
CVPR24(28805-28815)
IEEE DOI 2410
Training, Perturbation methods, Predictive models, Benchmark testing, Robustness, defense BibRef

Xu, X.Y.[Xiao-Yang], Yang, M.[Mengda], Yi, W.Z.[Wen-Zhe], Li, Z.[Ziang], Wang, J.[Juan], Hu, H.X.[Hong-Xin], Zhuang, Y.[Yong], Liu, Y.X.[Ya-Xin],
A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack Against Split Learning,
CVPR24(12130-12139)
IEEE DOI 2410
Computer aided instruction, Distance learning, Transfer learning, Training data, Privacy breach, Feature extraction BibRef

Ho, S.T.[Sy-Tuyen], Hao, K.J.[Koh Jun], Chandrasegaran, K.[Keshigeyan], Nguyen, N.B.[Ngoc-Bao], Cheung, N.M.[Ngai-Man],
Model Inversion Robustness: Can Transfer Learning Help?,
CVPR24(12183-12193)
IEEE DOI Code:
WWW Link. 2410
Training, Degradation, Privacy, Transfer learning, Training data, Minimization, Data models, Transparency, fairness, accountability, ethics in vision BibRef

Franchi, G.[Gianni], Laurent, O.[Olivier], Leguéry, M.[Maxence], Bursuc, A.[Andrei], Pilzer, A.[Andrea], Yao, A.[Angela],
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models,
CVPR24(12194-12204)
IEEE DOI 2410
Training, Uncertainty, Computational modeling, Semantic segmentation, Transfer learning, Transforms, Scalable Strategy BibRef

Zhou, X.[Xin], Liang, D.K.[Ding-Kang], Xu, W.[Wei], Zhu, X.K.[Xing-Kui], Xu, Y.[Yihan], Zou, Z.K.[Zhi-Kang], Bai, X.[Xiang],
Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis,
CVPR24(14707-14717)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Training, Adaptation models, Computational modeling, Transfer learning, Graphics processing units BibRef

Bär, A.[Andreas], Houlsby, N.[Neil], Dehghani, M.[Mostafa], Kumar, M.[Manoj],
Frozen Feature Augmentation for Few-Shot Image Classification,
CVPR24(16046-16057)
IEEE DOI 2410
Training, Brightness, Transfer learning, Data augmentation, Transformers, image classification, data augmentation BibRef

Wu, Z.F.[Zhi-Fan], Mao, C.J.[Chao-Jie], Wang, X.[Xue], Jiang, J.W.[Jian-Wen], Lv, Y.[Yiliang], Jin, R.[Rong],
Structured Model Probing: Empowering Efficient Transfer Learning by Structured Regularization,
CVPR24(16838-16847)
IEEE DOI 2410
Adaptation models, Computational modeling, Transfer learning, Switched mode power supplies, Predictive models, Complexity theory BibRef

Li, Y.[Yun], Liu, Z.[Zhe], Chen, H.[Hang], Yao, L.[Lina],
Context-Based and Diversity-Driven Specificity in Compositional Zero-Shot Learning,
CVPR24(17037-17046)
IEEE DOI 2410
Accuracy, Zero-shot learning, Filtering, Computational modeling, compositional zero-shot learning, transfer learning BibRef

Zhang, Y.[Yunhua], Doughty, H.[Hazel], Snoek, C.G.M.[Cees G. M.],
Low-Resource Vision Challenges for Foundation Models,
CVPR24(21956-21966)
IEEE DOI Code:
WWW Link. 2410
Deep learning, Transfer learning, Benchmark testing, Data augmentation, Natural language processing, Data models BibRef

Dai, M.Y.[Meng-Yu], Raffiee, A.H.[Amir Hossein], Jain, A.[Aashish], Correa, J.[Joshua],
Evaluating Transferability in Retrieval Tasks: An Approach Using MMD and Kernel Methods,
CVPR24(22390-22400)
IEEE DOI 2410
Measurement, Transfer learning, Search engines, Kernel BibRef

Liu, J.[Jihao], Zheng, J.L.[Jin-Liang], Liu, Y.[Yu], Li, H.S.[Hong-Sheng],
GLID: Pre-training a Generalist Encoder-Decoder Vision Model,
CVPR24(22851-22860)
IEEE DOI 2410
Training, Adaptation models, Image segmentation, Computational modeling, Transfer learning, Pose estimation BibRef

Do, D.P.[Dinh Phat], Kim, T.[Taehoon], Na, J.[Jaemin], Kim, J.[Jiwon], Lee, K.[Keonho], Cho, K.[Kyunghwan], Hwang, W.J.[Won-Jun],
D3T: Distinctive Dual-Domain Teacher Zigzagging Across RGB-Thermal Gap for Domain-Adaptive Object Detection,
CVPR24(23313-23322)
IEEE DOI Code:
WWW Link. 2410
Training, Adaptation models, Technological innovation, Protocols, Navigation, Source coding, Machine vision, Transfer learning BibRef

Yang, L.X.[Ling-Xiao], Zhang, R.Y.[Ru-Yuan], Wang, Y.C.[Yan-Chen], Xie, X.H.[Xiao-Hua],
MMA: Multi-Modal Adapter for Vision-Language Models,
CVPR24(23826-23837)
IEEE DOI Code:
WWW Link. 2410
Training, Visualization, Codes, Transfer learning, Semantics, Transformers, Multi-Modal, Vision-Language Models, Adapter BibRef

Hua, A.D.[An-Dong], Gu, J.D.[Jin-Dong], Xue, Z.Y.[Zhi-Yu], Carlini, N.[Nicholas], Wong, E.[Eric], Qin, Y.[Yao],
Initialization Matters for Adversarial Transfer Learning,
CVPR24(24831-24840)
IEEE DOI Code:
WWW Link. 2410
Training, Head, Codes, Transfer learning, Robustness BibRef

Ngo, B.H.[Ba Hung], Do-Tran, N.T.[Nhat-Tuong], Nguyen, T.N.[Tuan-Ngoc], Jeon, H.G.[Hae-Gon], Choi, T.J.[Tae Jong],
Learning CNN on ViT: A Hybrid Model to Explicitly Class-Specific Boundaries for Domain Adaptation,
CVPR24(28545-28554)
IEEE DOI 2410
Adaptation models, Accuracy, Heuristic algorithms, Design methodology, Benchmark testing, Transformers, transfer learning BibRef

Hu, Z.X.[Zi-Xuan], Li, X.T.[Xiao-Tong], Tang, S.X.[Shi-Xiang], Liu, J.[Jun], Hu, Y.C.[Yi-Chun], Duan, L.Y.[Ling-Yu],
LEAD: Exploring Logit Space Evolution for Model Selection,
CVPR24(28664-28673)
IEEE DOI 2410
Adaptation models, Computational modeling, Lead, Predictive models, Ordinary differential equations, Mathematical models, Transfer learning BibRef

Fu, M.H.[Ming-Hao], Zhu, K.[Ke],
Instance-based Max-margin for Practical Few-shot Recognition,
CVPR24(28674-28683)
IEEE DOI 2410
Training, Noise, Few shot learning, Few-shot Learning, Transfer Learning BibRef

Diao, H.[Haiwen], Wan, B.[Bo], Zhang, Y.[Ying], Jia, X.[Xu], Lu, H.C.[Hu-Chuan], Chen, L.[Long],
UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory,
CVPR24(28729-28740)
IEEE DOI Code:
WWW Link. 2410
Training, Backpropagation, Cross layer design, Codes, Scalability, Memory management BibRef

Daroya, R.[Rangel], Sun, A.[Aaron], Maji, S.[Subhransu],
Task2Box: Box Embeddings for Modeling Asymmetric Task Relationships,
CVPR24(28827-28837)
IEEE DOI 2410
Training, Visualization, Adaptation models, Computational modeling, Face recognition, Transfer learning, task representation, dataset visualization BibRef

Wei, C.[Chuheng], Wu, G.Y.[Guo-Yuan], Barth, M.J.[Matthew J.],
Feature Corrective Transfer Learning: End-to-End Solutions to Object Detection in Non-Ideal Visual Conditions,
UG24(23-32)
IEEE DOI 2410
Visualization, Accuracy, Computational modeling, Surveillance, Transfer learning, Imaging, Transfer Learning, Feature Correction, Non-Ideal Visual Conditions BibRef

Reyes-Amezcua, I.[Ivan], Ochoa-Ruiz, G.[Gilberto], Mendez-Vazquez, A.[Andres],
Enhancing Image Classification Robustness through Adversarial Sampling with Delta Data Augmentation (DDA),
LXCV24(274-283)
IEEE DOI 2410
Training, Deep learning, Perturbation methods, Resists, Predictive models, Data augmentation, Robustness, transfer learning BibRef

Zuo, Z.M.[Zhe-Ming], Smith, J.[Joseph], Stonehouse, J.[Jonathan], Obara, B.[Boguslaw],
Robust and Explainable Fine-Grained Visual Classification with Transfer Learning: A Dual-Carriageway Framework,
FaDE-TCV24(183-193)
IEEE DOI 2410
Training, Deep learning, Visualization, Accuracy, Image color analysis, Explainable AI, Transfer learning, robustness BibRef

Chen, H.[Hao], Tao, R.[Ran], Zhang, H.[Han], Wang, Y.D.[Yi-Dong], Li, X.[Xiang], Ye, W.[Wei], Wang, J.D.[Jin-Dong], Hu, G.S.[Guo-Sheng], Savvides, M.[Marios],
Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets,
Prompting24(1551-1561)
IEEE DOI 2410
Transfer learning, Modulation, Transformers, Natural language processing, Robustness BibRef

Belouadah, E.[Eden], Dapogny, A.[Arnaud], Bailly, K.[Kevin],
MultIOD: Rehearsal-free Multihead Incremental Object Detector,
CLVision24(4107-4117)
IEEE DOI 2410
Knowledge engineering, Transfer learning, Semantics, Neural networks, Detectors, Object detection, EfficientNet BibRef

Menta, T.R.[Tarun Ram], Jandial, S.[Surgan], Patil, A.[Akash], Bachu, S.[Saketh], Vimal, K.B., Krishnamurthy, B.[Balaji], Balasubramanian, V.N.[Vineeth N.], Sarkar, M.[Mausoom], Agarwal, C.[Chirag],
Active Transferability Estimation,
L3D-IVU24(2659-2670)
IEEE DOI 2410
Measurement, Computational modeling, Transfer learning, Estimation BibRef

Yang, Y.D.[Yue-Dong], Chiang, H.Y.[Hung-Yueh], Li, G.H.[Gui-Hong], Marculescu, D.[Diana], Marculescu, R.[Radu],
Cache and Reuse: Rethinking the Efficiency of On-device Transfer Learning,
ECV24(8040-8049)
IEEE DOI 2410
Training, Backpropagation, Accuracy, Transfer learning, Transformers BibRef

Nayman, N.[Niv], Golbert, A.[Avram], Noy, A.[Asaf], Zelnik-Manor, L.[Lihi],
Diverse Imagenet Models Transfer Better,
WACV24(1903-1914)
IEEE DOI 2404
Analytical models, Filters, Computer architecture, Task analysis, Algorithms, Machine learning architectures, formulations, Image recognition and understanding BibRef

Kender, J.R.[John R.], Dube, P.[Parijat], Han, Z.Y.[Zheng-Yang], Bhattacharjee, B.[Bishwaranjan],
G2L: A High-Dimensional Geometric Approach for Automatic Generation of Highly Accurate Pseudo-Labels,
LIMIT23(1085-1094)
IEEE DOI 2401
BibRef

Li, X.T.[Xiao-Tong], Hu, Z.X.[Zi-Xuan], Ge, Y.X.[Yi-Xiao], Shan, Y.[Ying], Duan, L.Y.[Ling-Yu],
Exploring Model Transferability through the Lens of Potential Energy,
ICCV23(5406-5415)
IEEE DOI Code:
WWW Link. 2401
BibRef

Xu, H.[Huiwen], Kang, U.,
Fast and Accurate Transferability Measurement by Evaluating Intra-class Feature Variance,
ICCV23(11440-11448)
IEEE DOI 2401
BibRef

Feng, Y.T.[Yu-Tong], Gong, B.[Biao], Jiang, J.W.[Jian-Wen], Lv, Y.[Yiliang], Shen, Y.J.[Yu-Jun], Zhao, D.L.[De-Li], Zhou, J.[Jingren],
ViM: Vision Middleware for Unified Downstream Transferring,
ICCV23(11662-11673)
IEEE DOI 2401
BibRef

Gholami, M.[Mohsen], Akbari, M.[Mohammad], Wang, X.[Xinglu], Kamranian, B.[Behnam], Zhang, Y.[Yong],
ETran: Energy-Based Transferability Estimation,
ICCV23(18567-18576)
IEEE DOI 2401
BibRef

Wang, H.Q.[Hao-Qi], Li, Z.Z.[Zhi-Zhong], Zhang, W.[Wayne],
Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation,
ICCV23(22421-22430)
IEEE DOI Code:
WWW Link. 2401
BibRef

Pégeot, T.[Tom], Kucher, I.[Inna], Popescu, A.[Adrian], Delezoide, B.[Bertrand],
A Comprehensive Study of Transfer Learning under Constraints,
REDLCV23(1140-1149)
IEEE DOI 2401
BibRef

Sama, N.[Nico], David, E.[Etienne], Rossetti, S.[Simone], Antona, A.[Alessandro], Franchetti, B.[Benjamin], Pirri, F.[Fiora],
A new large dataset and a transfer learning methodology for plant phenotyping in Vertical Farms,
CVPPA23(540-551)
IEEE DOI 2401
BibRef

Borup, K.[Kenneth], Phoo, C.P.[Cheng Perng], Hariharan, B.[Bharath],
Distilling from Similar Tasks for Transfer Learning on a Budget,
ICCV23(11397-11407)
IEEE DOI 2401
BibRef

Koh, S.[Seunghee], Shon, H.[Hyounguk], Lee, J.[Janghyeon], Hong, H.G.[Hyeong Gwon], Kim, J.[Junmo],
Disposable Transfer Learning for Selective Source Task Unlearning,
ICCV23(11718-11726)
IEEE DOI 2401
BibRef

Qing, Z.W.[Zhi-Wu], Zhang, S.W.[Shi-Wei], Huang, Z.Y.[Zi-Yuan], Zhang, Y.[Yingya], Gao, C.X.[Chang-Xin], Zhao, D.L.[De-Li], Sang, N.[Nong],
Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning,
ICCV23(13888-13898)
IEEE DOI Code:
WWW Link. 2401
BibRef

Deng, A.D.[An-Dong], Li, X.J.[Xing-Jian], Hu, D.[Di], Wang, T.Y.[Tian-Yang], Xiong, H.[Haoyi], Xu, C.Z.[Cheng-Zhong],
Towards Inadequately Pre-trained Models in Transfer Learning,
ICCV23(19340-19351)
IEEE DOI 2401
BibRef

Huizinga, W.[Wyke], Kruithof, M.[Maarten], Burghouts, G.[Gertjan], Schutte, K.[Klamer],
Efficient Transfer by Robust Label Selection and Learning with Pseudo-Labels,
ICIP23(2660-2664)
IEEE DOI 2312
BibRef

Tian, Y.L.[Yu-Long], Suya, F.[Fnu], Suri, A.[Anshuman], Xu, F.Y.[Feng-Yuan], Evans, D.[David],
Manipulating Transfer Learning for Property Inference,
CVPR23(15975-15984)
IEEE DOI 2309
BibRef

Tu, C.H.[Cheng-Hao], Mai, Z.[Zheda], Chao, W.L.[Wei-Lun],
Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning,
CVPR23(7725-7735)
IEEE DOI 2309
BibRef

Jain, S.[Saachi], Salman, H.[Hadi], Khaddaj, A.[Alaa], Wong, E.[Eric], Park, S.M.[Sung Min], Madry, A.[Aleksander],
A Data-Based Perspective on Transfer Learning,
CVPR23(3613-3622)
IEEE DOI 2309
BibRef

Nassar, I.[Islam], Hayat, M.[Munawar], Abbasnejad, E.[Ehsan], Rezatofighi, H.[Hamid], Harandi, M.[Mehrtash], Haffari, G.[Gholamreza],
LAVA:Label-efficient Visual Learning and Adaptation,
WACV23(147-156)
IEEE DOI 2302
Visualization, Technological innovation, Protocols, Semantics, Transfer learning, Object detection, Vision + language and/or other modalities BibRef

Moon, S.H.[Su-Hong], Buracas, D.[Domas], Park, S.H.[Seung-Hyun], Kim, J.[Jinkyu], Canny, J.[John],
An Embedding-Dynamic Approach to Self-Supervised Learning,
WACV23(2749-2757)
IEEE DOI 2302
Training, Semantic segmentation, Force, Dynamics, Transfer learning, Self-supervised learning, Object detection, and algorithms (including transfer) BibRef

Lee, H.J.[Hyun-Jae], Lee, G.[Gihyeon], Kim, J.[Junhwan], Cho, S.J.[Sung-Jun], Kim, D.[Dohyun], Yoo, D.[Donggeun],
Improving Multi-fidelity Optimization with a Recurring Learning Rate for Hyperparameter Tuning,
WACV23(2308-2317)
IEEE DOI 2302
Training, Schedules, Transfer learning, Optimization methods, Semisupervised learning, Convolutional neural networks, visual reasoning BibRef

Zengeler, N.[Nico], Glasmachers, T.[Tobias], Handmann, U.[Uwe],
Transfer Meta Learning,
ICPR22(4471-4478)
IEEE DOI 2212
Reuse previous knowledge. Systematics, Source coding, Transfer learning, Metadata, Predictive models, Multilayer perceptrons BibRef

Xu, C.F.[Chen-Feng], Yang, S.[Shijia], Galanti, T.[Tomer], Wu, B.[Bichen], Yue, X.Y.[Xiang-Yu], Zhai, B.[Bohan], Zhan, W.[Wei], Vajda, P.[Peter], Keutzer, K.[Kurt], Tomizuka, M.[Masayoshi],
Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models,
ECCV22(XXXVII:638-656).
Springer DOI 2211

WWW Link. Explore transfer of 2D to 3D. BibRef

Ding, N.[Nan], Chen, X.[Xi], Levinboim, T.[Tomer], Changpinyo, S.[Soravit], Soricut, R.[Radu],
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks,
ECCV22(XXXIV:252-268).
Springer DOI 2211
BibRef

Shao, W.Q.[Wen-Qi], Zhao, X.[Xun], Ge, Y.X.[Yi-Xiao], Zhang, Z.Y.[Zhao-Yang], Yang, L.[Lei], Wang, X.G.[Xiao-Gang], Shan, Y.[Ying], Luo, P.[Ping],
Not All Models Are Equal: Predicting Model Transferability in a Self-challenging Fisher Space,
ECCV22(XXXIV:286-302).
Springer DOI 2211
BibRef

Agostinelli, A.[Andrea], Pándy, M.[Michal], Uijlings, J.[Jasper], Mensink, T.[Thomas], Ferrari, V.[Vittorio],
How Stable Are Transferability Metrics Evaluations?,
ECCV22(XXXIV:303-321).
Springer DOI 2211
BibRef

Yu, P.C.[Ping-Chung], Sun, C.[Cheng], Sun, M.[Min],
Data Efficient 3D Learner via Knowledge Transferred from 2D Model,
ECCV22(XXIX:182-198).
Springer DOI 2211
BibRef

Cui, Q.[Quan], Zhao, B.C.[Bing-Chen], Chen, Z.M.[Zhao-Min], Zhao, B.R.[Bo-Rui], Song, R.J.[Ren-Jie], Zhou, B.Y.[Bo-Yan], Liang, J.J.[Jia-Jun], Yoshie, O.[Osamu],
Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective,
ECCV22(XXVI:20-37).
Springer DOI 2211
BibRef

Idris, A.[Azeez], Khaleel, M.[Mohammed], Tavanapong, W.[Wallapak], Oh, J.[JungHwan], de Groen, P.[Piet],
Training Strategy for Limited Labeled Data by Learning from Confusion,
ICIP22(1926-1930)
IEEE DOI 2211
Training, Deep learning, Costs, Transfer learning, Supervised learning, Training data, Weak Supervision, Training Strategy BibRef

Jiang, Z.Y.[Zi-Yu], Chen, T.L.[Tian-Long], Chen, X.[Xuxi], Cheng, Y.[Yu], Zhou, L.[Luowei], Yuan, L.[Lu], Awadallah, A.[Ahmed], Wang, Z.Y.[Zhang-Yang],
DnA: Improving Few-Shot Transfer Learning with Low-Rank Decomposition and Alignment,
ECCV22(XX:239-256).
Springer DOI 2211
BibRef

Ahmed, S.M.[Sk Miraj], Lohit, S.[Suhas], Peng, K.C.[Kuan-Chuan], Jones, M.J.[Michael J.], Roy-Chowdhury, A.K.[Amit K.],
Cross-Modal Knowledge Transfer Without Task-Relevant Source Data,
ECCV22(XXXIV:111-127).
Springer DOI 2211
BibRef

Sinha, S.[Samarth], Roth, K.[Karsten], Goyal, A.[Anirudh], Ghassemi, M.[Marzyeh], Akata, Z.[Zeynep], Larochelle, H.[Hugo], Garg, A.[Animesh],
Uniform Priors for Data-Efficient Learning,
L3D-IVU22(4016-4027)
IEEE DOI 2210
Measurement, Training, Deep learning, Adaptation models, Scalability, Machine vision, Transfer learning BibRef

Zhai, X.H.[Xiao-Hua], Wang, X.[Xiao], Mustafa, B.[Basil], Steiner, A.[Andreas], Keysers, D.[Daniel], Kolesnikov, A.[Alexander], Beyer, L.[Lucas],
LiT: Zero-Shot Transfer with Locked-Image text Tuning,
CVPR22(18102-18112)
IEEE DOI 2210
Training, Representation learning, Adaptation models, Computational modeling, Transformers, Data models, Transfer/low-shot/long-tail learning BibRef

Agostinelli, A.[Andrea], Uijlings, J.[Jasper], Mensink, T.[Thomas], Ferrari, V.[Vittorio],
Transferability Metrics for Selecting Source Model Ensembles,
CVPR22(7926-7936)
IEEE DOI 2210
Measurement, Training, Image segmentation, Computational modeling, Transfer learning, Semantics, Deep learning architectures and techniques BibRef

Lu, Y.N.[Yu-Ning], Liu, J.Z.[Jian-Zhuang], Zhang, Y.G.[Yong-Gang], Liu, Y.J.[Ya-Jing], Tian, X.M.[Xin-Mei],
Prompt Distribution Learning,
CVPR22(5196-5205)
IEEE DOI 2210
Training, Visualization, Adaptation models, Gaussian distribution, Task analysis, Vision+language, Transfer/low-shot/long-tail learning BibRef

Byun, J.[Junyoung], Cho, S.[Seungju], Kwon, M.J.[Myung-Joon], Kim, H.S.[Hee-Seon], Kim, C.[Changick],
Improving the Transferability of Targeted Adversarial Examples through Object-Based Diverse Input,
CVPR22(15223-15232)
IEEE DOI 2210
Solid modeling, Image recognition, Codes, Face recognition, Computational modeling, Adversarial attack and defense, Machine learning BibRef

Yang, M.[Muli], Zhu, Y.[Yuehua], Yu, J.P.[Jia-Ping], Wu, A.[Aming], Deng, C.[Cheng],
Divide and Conquer: Compositional Experts for Generalized Novel Class Discovery,
CVPR22(14248-14257)
IEEE DOI 2210
Training, Annotations, Semantics, Benchmark testing, Task analysis, Recognition: detection, Self- semi- meta- Transfer/low-shot/long-tail learning BibRef

Garau, N.[Nicola], Bisagno, N.[Niccoló], Sambugaro, Z.[Zeno], Conci, N.[Nicola],
Interpretable part-whole hierarchies and conceptual-semantic relationships in neural networks,
CVPR22(13679-13688)
IEEE DOI 2210
Deep learning, Visualization, Shape, Neural networks, Behavioral sciences, Transfer/low-shot/long-tail learning BibRef

Iofinova, E.[Eugenia], Peste, A.[Alexandra], Kurtz, M.[Mark], Alistarh, D.[Dan],
How Well Do Sparse ImageNet Models Transfer?,
CVPR22(12256-12266)
IEEE DOI 2210
Training, Adaptation models, Image coding, Transfer learning, Convolutional neural networks, Transfer/low-shot/long-tail learning BibRef

Yang, L.[Li], Rakin, A.S.[Adnan Siraj], Fan, D.L.[De-Liang],
RepNet: Efficient On-Device Learning via Feature Reprogramming,
CVPR22(12267-12276)
IEEE DOI 2210
Training, Connectors, Deep learning, Computational modeling, Transfer learning, Memory management, Transfer/low-shot/long-tail learning BibRef

Pándy, M.[Michal], Agostinelli, A.[Andrea], Uijlings, J.[Jasper], Ferrari, V.[Vittorio], Mensink, T.[Thomas],
Transferability Estimation using Bhattacharyya Class Separability,
CVPR22(9162-9172)
IEEE DOI 2210
Measurement, Adaptation models, Image segmentation, Computational modeling, Transfer learning, Semantics, Transfer/low-shot/long-tail learning BibRef

Wang, Y.Z.[Yi-Zhou], Tang, S.X.[Shi-Xiang], Zhu, F.[Feng], Bai, L.[Lei], Zhao, R.[Rui], Qi, D.L.[Dong-Lian], Ouyang, W.L.[Wan-Li],
Revisiting the Transferability of Supervised Pretraining: An MLP Perspective,
CVPR22(9173-9183)
IEEE DOI 2210
Visualization, Redundancy, Pipelines, Object detection, Multilayer perceptrons, Benchmark testing, Transfer/low-shot/long-tail learning BibRef

Renggli, C.[Cedric], Pinto, A.S.[André Susano], Rimanic, L.[Luka], Puigcerver, J.[Joan], Riquelme, C.[Carlos], Zhang, C.[Ce], Lucic, M.[Mario],
Which Model to Transfer? Finding the Needle in the Growing Haystack,
CVPR22(9195-9204)
IEEE DOI 2210
Training, Solid modeling, Computational modeling, Transfer learning, Search problems, Solids, Transfer/low-shot/long-tail learning BibRef

Vaze, S.[Sagar], Hant, K.[Kai], Vedaldi, A.[Andrea], Zisserman, A.[Andrew],
Generalized Category Discovery,
CVPR22(7482-7491)
IEEE DOI 2210
Representation learning, Image recognition, Limiting, Codes, Semantics, Clustering algorithms, Recognition: detection, Self- semi- meta- Transfer/low-shot/long-tail learning BibRef

Rajeswar, S.[Sai], Rodríguez, P.[Pau], Singhal, S.[Soumye], Vazquez, D.[David], Courville, A.[Aaron],
Multi-label Iterated Learning for Image Classification with Label Ambiguity,
CVPR22(4773-4783)
IEEE DOI 2210
Training, Visualization, Systematics, Computational modeling, Transfer learning, Predictive models, Recognition: detection, Visual reasoning BibRef

Yazdanpanah, M.[Moslem], Rahman, A.A.[Aamer Abdul], Chaudhary, M.[Muawiz], Desrosiers, C.[Christian], Havaei, M.[Mohammad], Belilovsky, E.[Eugene], Kahou, S.E.[Samira Ebrahimi],
Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning,
CVPR22(9099-9108)
IEEE DOI 2210
Training, Machine vision, Transfer learning, Statistical distributions, Robustness, Vision applications and systems BibRef

Conder, J.[Jonathan], Jefferson, J.[Josephine], Pages, N.[Nathan], Jawed, K.[Khurram], Nejati, A.[Alireza], Sagar, M.[Mark],
Efficient Transfer Learning for Visual Tasks via Continuous Optimization of Prompts,
CIAP22(I:297-309).
Springer DOI 2205
BibRef

Schöntag, P.[Patricia], Nakath, D.[David], Röhrl, S.[Stefan], Köser, K.[Kevin],
Towards Cross Domain Transfer Learning for Underwater Correspondence Search,
CIAP22(III:461-472).
Springer DOI 2205
BibRef

Xu, S.C.[Shi-Chao], Wang, L.[Lixu], Wang, Y.X.[Yi-Xuan], Zhu, Q.[Qi],
Weak Adaptation Learning: Addressing Cross-domain Data Insufficiency with Weak Annotator,
ICCV21(8897-8906)
IEEE DOI 2203
Learning systems, Labeling, Task analysis, Transfer/Low-shot/Semi/Unsupervised Learning, Machine learning architectures and formulations BibRef

Zhuang, W.M.[Wei-Ming], Gan, X.[Xin], Wen, Y.G.[Yong-Gang], Zhang, S.[Shuai], Yi, S.[Shuai],
Collaborative Unsupervised Visual Representation Learning from Decentralized Data,
ICCV21(4892-4901)
IEEE DOI 2203
Representation learning, Training, Data privacy, Visualization, Protocols, Aggregates, Mobile handsets, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Sun, Q.[Qi], Bai, C.[Chen], Chen, T.H.[Ting-Huan], Geng, H.[Hao], Zhang, X.Y.[Xin-Yun], Bai, Y.[Yang], Yu, B.[Bei],
Fast and Efficient DNN Deployment via Deep Gaussian Transfer Learning,
ICCV21(5360-5370)
IEEE DOI 2203
Knowledge engineering, Computational modeling, Transfer learning, Neural networks, Gaussian processes, Inference algorithms, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Greer, H.[Hastings], Kwitt, R.[Roland], Vialard, F.X.[François-Xavier], Niethammer, M.[Marc],
ICON: Learning Regular Maps Through Inverse Consistency,
ICCV21(3376-3385)
IEEE DOI 2203
Representation learning, Solid modeling, Computational modeling, Sociology, Loss measurement, Task analysis, Medical, biological, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Hong, G.Z.[Guan-Zhe], Mao, Z.Y.[Zhi-Yuan], Lin, X.J.[Xiao-Jun], Chan, S.H.[Stanley H.],
Student-Teacher Learning from Clean Inputs to Noisy Inputs,
CVPR21(12070-12079)
IEEE DOI 2111
Training, Learning systems, Knowledge engineering, Systematics, Protocols, Numerical analysis BibRef

Klopp, J.P.[Jan P.], Liu, K.C.[Keng-Chi], Chen, L.G.[Liang-Gee], Chien, S.Y.[Shao-Yi],
How to Exploit the Transferability of Learned Image Compression to Conventional Codecs,
CVPR21(16160-16169)
IEEE DOI 2111
Image coding, Codecs, Pipelines, Signal processing algorithms, Generative adversarial networks, Distortion, Loss measurement BibRef

Eckart, B.[Benjamin], Yuan, W.T.[Wen-Tao], Liu, C.[Chao], Kautz, J.[Jan],
Self-Supervised Learning on 3D Point Clouds by Learning Discrete Generative Models,
CVPR21(8244-8253)
IEEE DOI 2111
Adaptation models, Solid modeling, Computational modeling, Transfer learning, Semantics, Neural networks BibRef

Xu, Q.W.[Qin-Wei], Zhang, R.P.[Rui-Peng], Zhang, Y.[Ya], Wang, Y.F.[Yan-Feng], Tian, Q.[Qi],
A Fourier-based Framework for Domain Generalization,
CVPR21(14378-14387)
IEEE DOI 2111
Degradation, Deep learning, Semantics, Force, Training data, Focusing BibRef

Han, D.Y.[Dong-Yoon], Choe, J.[Junsuk], Chun, S.[Seonghyeok], Chung, J.J.Y.[John Joon Young], Chang, M.[Minsuk], Yun, S.[Sangdoo], Song, J.Y.[Jean Y.], Oh, S.J.[Seong Joon],
Neglected Free Lunch: Learning Image Classifiers Using Annotation Byproducts,
ICCV23(20143-20155)
IEEE DOI 2401
BibRef

Yun, S.[Sangdoo], Oh, S.J.[Seong Joon], Heo, B.[Byeongho], Han, D.Y.[Dong-Yoon], Choe, J.[Junsuk], Chun, S.[Sanghyuk],
Re-labeling ImageNet: From Single to Multi-Labels, from Global to Localized Labels,
CVPR21(2340-2350)
IEEE DOI 2111
Training, Visualization, Costs, Annotations, Transfer learning, Crops, Transforms BibRef

Pouransari, H.[Hadi], Javaheripi, M.[Mojan], Sharma, V.[Vinay], Tuzel, O.[Oncel],
Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution,
ECV21(3026-3036)
IEEE DOI 2109
Training, Uncertainty, Neural networks, Estimation, Data models, Task analysis BibRef

de la Comble, A.[Aloïs], Prepin, K.[Ken],
Efficient transfer learning for multi-channel convolutional neural networks,
MVA21(1-6)
DOI Link 2109
Training, Image sensors, Perturbation methods, Transfer learning, Network architecture BibRef

Hou, J.[Jinyong], Deng, J.D.[Jeremiah D.], Cranefield, S.[Stephen], Ding, X.J.[Xue-Jie],
Cross-Domain Latent Modulation for Variational Transfer Learning,
WACV21(3148-3157)
IEEE DOI 2106
Adaptation models, Visualization, Perturbation methods, Transfer learning, Modulation BibRef

Wei, P.F.[Peng-Fei], Leong, T.Y.[Tze Yun],
Randomized Transferable Machine,
ICPR21(8711-8718)
IEEE DOI 2105
Training, Sociology, Transfer learning, Training data, Data models, Noise measurement BibRef

Marini, N.[Niccolò], Otálora, S.[Sebastian], Müller, H.[Henning], Atzori, M.[Manfredo],
Semi-supervised Learning with a Teacher-Student Paradigm for Histopathology Classification: A Resource to Face Data Heterogeneity and Lack of Local Annotations,
AIDP20(105-119).
Springer DOI 2103
BibRef

Rahimi, A.[Amir], Shaban, A.[Amirreza], Ajanthan, T.[Thalaiyasingam], Hartley, R.I.[Richard I.], Boots, B.[Byron],
Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization,
ECCV20(XXIV:395-412).
Springer DOI 2012
BibRef

Sun, M.[Ming], Dou, H.X.[Hao-Xuan], Yan, J.J.[Jun-Jie],
Efficient Transfer Learning via Joint Adaptation of Network Architecture and Weight,
ECCV20(XIII:463-480).
Springer DOI 2011
BibRef

Wang, W., Zhai, W., Cao, Y.,
Deep Inhomogeneous Regularization For Transfer Learning,
ICIP20(221-225)
IEEE DOI 2011
Training, Aircraft, Task analysis, Nonhomogeneous media, Optimization, Automobiles, Neural networks, Transfer Learning, Deep Learning BibRef

Zhong, Y.Y.[Yuan-Yi], Wang, J.F.[Jian-Feng], Peng, J.[Jian], Zhang, L.[Lei],
Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer,
ECCV20(XXVI:615-631).
Springer DOI 2011
BibRef

Dwivedi, K.[Kshitij], Huang, J.H.[Jia-Hui], Cichy, R.M.[Radoslaw Martin], Roig, G.[Gemma],
Duality Diagram Similarity: A Generic Framework for Initialization Selection in Task Transfer Learning,
ECCV20(XXVI:497-513).
Springer DOI 2011
BibRef

Luo, S.[Sihui], Pan, W.W.[Wen-Wen], Wang, X.C.[Xin-Chao], Wang, D.Z.[Da-Zhou], Tang, H.H.[Hai-Hong], Song, M.L.[Ming-Li],
Collaboration by Competition: Self-coordinated Knowledge Amalgamation for Multi-Talent Student Learning,
ECCV20(VI:631-646).
Springer DOI 2011
BibRef

Chen, L.C.[Liang-Chieh], Lopes, R.G.[Raphael Gontijo], Cheng, B.[Bowen], Collins, M.D.[Maxwell D.], Cubuk, E.D.[Ekin D.], Zoph, B.[Barret], Adam, H.[Hartwig], Shlens, J.[Jonathon],
Naive-Student: Leveraging Semi-supervised Learning in Video Sequences for Urban Scene Segmentation,
ECCV20(IX:695-714).
Springer DOI 2011
semi-supervised learning in unlabeled video sequences and extra images to improve the performance on urban scene segmentation. BibRef

Zhao, L.[Long], Peng, X.[Xi], Chen, Y.X.[Yu-Xiao], Kapadia, M.[Mubbasir], Metaxas, D.N.[Dimitris N.],
Knowledge As Priors: Cross-Modal Knowledge Generalization for Datasets Without Superior Knowledge,
CVPR20(6527-6536)
IEEE DOI 2008
Knowledge engineering, Pose estimation, Training, Neural networks, Probabilistic logic, Maximum likelihood estimation BibRef

Wang, Y., Chen, X., You, Y., Li, L.E., Hariharan, B., Campbell, M., Weinberger, K.Q.[Kilian Q.], Chao, W.,
Train in Germany, Test in the USA: Making 3D Object Detectors Generalize,
CVPR20(11710-11720)
IEEE DOI 2008
Laser radar, Automobiles, Detectors, Object detection, Cameras, Training BibRef

Bhattacharjee, B., Render, J.R., Hill, M., Dube, P., Huo, S., Glass, M.R., Belgodere, B., Pankanti, S., Codella, N., Watson, P.,
P2L: Predicting Transfer Learning for Images and Semantic Relations,
DeepVision20(3284-3293)
IEEE DOI 2008
Task analysis, Training, Computational modeling, Data models, Machine learning, Adaptation models, Semantics BibRef

Zhong, Y., Maki, A.,
Regularizing CNN Transfer Learning With Randomised Regression,
CVPR20(13634-13643)
IEEE DOI 2008
Task analysis, Training, Image representation, Adaptation models, Neurons, Data models BibRef

Yan, X., Acuna, D., Fidler, S.,
Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data,
CVPR20(3892-3901)
IEEE DOI 2008
Servers, Data models, Task analysis, Computational modeling, Search engines, Training, Machine learning BibRef

Kim, Y., Soh, J.W., Park, G.Y., Cho, N.I.,
Transfer Learning From Synthetic to Real-Noise Denoising With Adaptive Instance Normalization,
CVPR20(3479-3489)
IEEE DOI 2008
Training, Noise level, Noise reduction, Convolution, Cameras, Pipelines, Image reconstruction BibRef

Royer, A., Lampert, C.H.,
A Flexible Selection Scheme for Minimum-Effort Transfer Learning,
WACV20(2180-2189)
IEEE DOI 2006
Task analysis, Training, Tuning, Feature extraction, Visualization, Knowledge engineering, Training data BibRef

Lamb, A.[Alex], Ozair, S.[Sherjil], Verma, V.[Vikas], Ha, D.[David],
SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks,
WACV20(952-961)
IEEE DOI 2006
Domain transfer applied to sketch recognition. Result are not great. Training, Task analysis, Cats, Dogs, Automobiles, Perturbation methods, Ear BibRef

Li, J., Xu, Z., Wang, Y., Zhao, Q., Kankanhalli, M.S.,
GradMix: Multi-source Transfer across Domains and Tasks,
WACV20(3008-3016)
IEEE DOI 2006
Task analysis, Training, Adaptation models, Silicon, Optimization, Training data BibRef

Bi, S.[Sai], Sunkavalli, K.[Kalyan], Perazzi, F.[Federico], Shechtman, E.[Eli], Kim, V.[Vladimir], Ramamoorthi, R.[Ravi],
Deep CG2Real: Synthetic-to-Real Translation via Image Disentanglement,
ICCV19(2730-2739)
IEEE DOI 2004
Train on synthetic. image processing, learning (artificial intelligence), two-stage pipeline, improved CycleGAN network, Training BibRef

Tran, A.T.[Anh Tuan], Nguyen, C.[Cuong], Hassner, T.[Tal],
Transferability and Hardness of Supervised Classification Tasks,
ICCV19(1395-1405)
IEEE DOI 2004
entropy, face recognition, image classification, learning (artificial intelligence), object recognition, Computational modeling BibRef

Wu, Y.W.[Yuan-Wei], Zhang, Z.M.[Zi-Ming], Wang, G.H.[Guang-Hui],
Unsupervised Deep Feature Transfer for Low Resolution Image Classification,
RLQ19(1065-1069)
IEEE DOI 2004
data structures, feature extraction, image classification, image enhancement, image resolution, neural nets, low resolution image classificatin BibRef

Li, K., Zhang, Y., Li, K., Li, Y., Fu, Y.,
Attention Bridging Network for Knowledge Transfer,
ICCV19(5197-5206)
IEEE DOI 2004
image segmentation, learning (artificial intelligence), neural nets, pattern classification, classification network, Knowledge transfer BibRef

Kuen, J., Perazzi, F., Lin, Z., Zhang, J., Tan, Y.,
Scaling Object Detection by Transferring Classification Weights,
ICCV19(6043-6052)
IEEE DOI 2004
feature extraction, genomics, image classification, information retrieval, learning (artificial intelligence), Knowledge engineering BibRef

Huang, H., Jain, V., Mehta, H., Ku, A., Magalhaes, G., Baldridge, J., Ie, E.,
Transferable Representation Learning in Vision-and-Language Navigation,
ICCV19(7403-7412)
IEEE DOI 2004
image sequences, learning (artificial intelligence), Length measurement BibRef

Durall, R., Pfreundt, F.J., Keuper, J.,
Semi Few-Shot Attribute Translation,
IVCNZ19(1-8)
IEEE DOI 2004
image processing, learning (artificial intelligence), semifew-shot attribute translation, image-to-image translation, generative transfer learning BibRef

Iqbal, A., Richard, A., Gall, J.,
Enhancing Temporal Action Localization with Transfer Learning from Action Recognition,
CoView19(1533-1540)
IEEE DOI 2004
feature extraction, image classification, image motion analysis, image segmentation, image sequences, inference mechanisms, Action Detection BibRef

Liu, B., Wu, Z., Hu, H., Lin, S.,
Deep Metric Transfer for Label Propagation with Limited Annotated Data,
MDALC19(1317-1326)
IEEE DOI 2004
Code, Learning.
WWW Link. image annotation, object recognition, unsupervised learning, deep metric transfer, limited annotated data, object class, self supervised learning BibRef

Jakubovitz, D., Rodrigues, M.R.D., Giryes, R.,
Lautum Regularization for Semi-Supervised Transfer Learning,
SDL-CV19(763-767)
IEEE DOI 2004
information theory, learning (artificial intelligence), neural nets, source dataset, deep neural network, Information Theory BibRef

Cicek, S., Soatto, S.,
Unsupervised Domain Adaptation via Regularized Conditional Alignment,
ICCV19(1416-1425)
IEEE DOI 2004
pattern classification, statistical distributions, unsupervised learning, classifier performance, Neural networks BibRef

Dwivedi, K.[Kshitij], Roig, G.[Gemma],
Representation Similarity Analysis for Efficient Task Taxonomy and Transfer Learning,
CVPR19(12379-12388).
IEEE DOI 2002
BibRef

Wang, Z.[Zirui], Dai, Z.H.[Zi-Hang], Poczos, B.[Barnabas], Carbonell, J.[Jaime],
Characterizing and Avoiding Negative Transfer,
CVPR19(11285-11294).
IEEE DOI 2002
BibRef

Chen, Y.C.[Yun-Chun], Lin, Y.Y.[Yen-Yu], Yang, M.H.[Ming-Hsuan], Huang, J.B.[Jia-Bin],
CrDoCo: Pixel-Level Domain Transfer With Cross-Domain Consistency,
CVPR19(1791-1800).
IEEE DOI 2002
BibRef

Wang, P.[Pei], Vasconcelos, N.M.[Nuno M.],
A Machine Teaching Framework for Scalable Recognition,
ICCV21(4925-4934)
IEEE DOI 2203
Crowdsourcing, Costs, Education, Pipelines, Data collection, Prediction algorithms, Vision applications and systems, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Li, Y.S.[Yun-Sheng], Vasconcelos, N.M.[Nuno M.],
Efficient Multi-Domain Learning by Covariance Normalization,
CVPR19(5419-5428).
IEEE DOI 2002
BibRef

Essich, M.[Michael], Ludl, D.[Dennis], Gulde, T.[Thomas], Curio, C.[Cristóbal],
Learning to Translate Between Real World and Simulated 3D Sensors While Transferring Task Models,
3DV19(681-689)
IEEE DOI 1911
Real data not like trained data Sensors, Data models, Task analysis, Adaptation models, Training, Character Animation BibRef

Coors, B.[Benjamin], Condurache, A.P.[Alexandru Paul], Geiger, A.[Andreas],
NoVA: Learning to See in Novel Viewpoints and Domains,
3DV19(116-125)
IEEE DOI 1911
Adaptation models, Task analysis, Estimation, Semantics, Image segmentation, Cameras, Geometry, Novel Viewpoint Adaptation, Viewpoint Invariance BibRef

Bao, Y., Li, Y., Huang, S., Zhang, L., Zheng, L., Zamir, A., Guibas, L.J.[Leonidas J.],
An Information-Theoretic Approach to Transferability in Task Transfer Learning,
ICIP19(2309-2313)
IEEE DOI 1910
Task transfer learning, Transferability, H-Score, Image recognition & classification BibRef

Deng, X.Q.[Xue-Qing], Zhu, Y.[Yi], Tian, Y.X.[Yu-Xin], Newsam, S.[Shawn],
Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery,
WACV21(2159-2168)
IEEE DOI 2106
Training, Earth, Image segmentation, Adaptation models, Semantics, Neural networks, Task analysis BibRef

Zhu, Y.[Yi], Xue, J.[Jia], Newsam, S.[Shawn],
Gated Transfer Network for Transfer Learning,
ACCV18(IV:354-369).
Springer DOI 1906
BibRef

Kim, J.[Jaekyum], Koh, J.[Junho], Kim, Y.[Yecheol], Choi, J.[Jaehyung], Hwang, Y.[Youngbae], Choi, J.W.[Jun Won],
Robust Deep Multi-modal Learning Based on Gated Information Fusion Network,
ACCV18(IV:90-106).
Springer DOI 1906
BibRef

Zhong, Y.[Yang], Li, V.[Vladimir], Okada, R.[Ryuzo], Maki, A.[Atsuto],
Target Aware Network Adaptation for Efficient Representation Learning,
CEFR-LCV18(IV:450-467).
Springer DOI 1905
Finding the CNN that works. BibRef

Okatani, T.[Takayuki], Liu, X.[Xing], Suganuma, M.[Masanori],
Improving Generalization Ability of Deep Neural Networks for Visual Recognition Tasks,
CCIW19(3-13).
Springer DOI 1905
BibRef

Sayed, N.[Nawid], Brattoli, B.[Biagio], Ommer, B.[Björn],
Cross and Learn: Cross-Modal Self-supervision,
GCPR18(228-243).
Springer DOI 1905
BibRef

Rahman, M.M.[Mohammad Mahfujur], Fookes, C.[Clinton], Baktashmotlagh, M.[Mahsa], Sridharan, S.[Sridha],
Multi-Component Image Translation for Deep Domain Generalization,
WACV19(579-588)
IEEE DOI 1904
image classification, learning (artificial intelligence), neural nets, protocols, protocol, synthetic images, Adaptation models BibRef

Chen, D., Liang, X., Wang, Y., Gao, W.,
Soft Transfer Learning via Gradient Diagnosis for Visual Relationship Detection,
WACV19(1118-1126)
IEEE DOI 1904
inference mechanisms, learning (artificial intelligence), object detection, optimisation, diverse language ambiguities, Dogs BibRef

Wang, T., Huan, J., Zhu, M.,
Instance-Based Deep Transfer Learning,
WACV19(367-375)
IEEE DOI 1904
image classification, learning (artificial intelligence), Load modeling BibRef

Li, J.S.[Jian-Shu], Zhou, P.[Pan], Chen, Y.P.[Yun-Peng], Zhao, J.[Jian], Roy, S.[Sujoy], Yan, S.C.[Shui-Cheng], Feng, J.S.[Jia-Shi], Sim, T.[Terence],
Task Relation Networks,
WACV19(932-940)
IEEE DOI 1904
covariance matrices, learning (artificial intelligence), task analysis, task covariance modeling, Heuristic algorithms
See also Estimation of Affective Level in the Wild with Multiple Memory Networks. BibRef

Zhang, Y.[Ying], Xiang, T.[Tao], Hospedales, T.M.[Timothy M.], Lu, H.C.[Hu-Chuan],
Deep Mutual Learning,
CVPR18(4320-4328)
IEEE DOI 1812
Training, Computational modeling, Task analysis, Supervised learning, Optimization, Entropy, Neural networks BibRef

Kundu, J.N.[Jogendra Nath], Uppala, P.K.[Phani Krishna], Pahuja, A.[Anuj], Babu, R.V.[R. Venkatesh],
AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation,
CVPR18(2656-2665)
IEEE DOI 1812
Task analysis, Estimation, Semantics, Adaptation models, Training, Predictive models. BibRef

Lee, K., He, X., Zhang, L., Yang, L.,
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise,
CVPR18(5447-5456)
IEEE DOI 1812
Noise measurement, Feature extraction, Training, Task analysis, Neural networks, Labeling, Manuals BibRef

Zamir, A.R., Sax, A., Cheerla, N., Suri, R., Cao, Z., Malik, J., Guibas, L.J.,
Robust Learning Through Cross-Task Consistency,
CVPR20(11194-11203)
IEEE DOI 2008
Task analysis, Training, Image edge detection, Neural networks, Uncertainty BibRef

Zamir, A.R., Sax, A., Shen, W., Guibas, L.J.[Leonidas J.], Malik, J., Savarese, S.,
Taskonomy: Disentangling Task Transfer Learning,
CVPR18(3712-3722)
IEEE DOI 1812
Award, CVPR. Task analysis, Computational modeling, Taxonomy, Dictionaries BibRef

Chen, S., Zhang, C., Dong, M.,
Coupled End-to-End Transfer Learning with Generalized Fisher Information,
CVPR18(4329-4338)
IEEE DOI 1812
Task analysis, Training, Decoding, Neural networks, Adaptation models, Image reconstruction, Feature extraction BibRef

Huang, X., Peng, Y.,
Deep Cross-Media Knowledge Transfer,
CVPR18(8837-8846)
IEEE DOI 1812
Media, Training, Correlation, Semantics, Adaptation models, Knowledge transfer, Computational modeling BibRef

Noroozi, M., Vinjimoor, A., Favaro, P., Pirsiavash, H.,
Boosting Self-Supervised Learning via Knowledge Transfer,
CVPR18(9359-9367)
IEEE DOI 1812
Task analysis, Computational modeling, Training, Feature extraction, Data models, Measurement BibRef

Mormont, R., Geurts, P., Marée, R.,
Comparison of Deep Transfer Learning Strategies for Digital Pathology,
Microscopy18(2343-234309)
IEEE DOI 1812
Feature extraction, Task analysis, Biomedical imaging, Training, Support vector machines BibRef

Lu, W., Chung, F.,
A Deep Graphical Model for Layered Knowledge Transfer,
ICPR18(260-265)
IEEE DOI 1812
Task analysis, Dictionaries, Adaptation models, Inference algorithms, Graphical models, Training BibRef

Passalis, N., Tefas, A.,
Neural Network Knowledge Transfer using Unsupervised Similarity Matching,
ICPR18(716-721)
IEEE DOI 1812
a Receivers, Knowledge transfer, Training, Knowledge engineering, Neural networks, Computational modeling, Geometry BibRef

Pan, X.G.[Xin-Gang], Luo, P.[Ping], Shi, J.P.[Jian-Ping], Tang, X.[Xiaoou],
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net,
ECCV18(II: 484-500).
Springer DOI 1810
Instance normalization and batch normalization for expanding domain. BibRef

Huang, H.S.[Hao-Shuo], Huang, Q.X.[Qi-Xing], Krähenbühl, P.[Philipp],
Domain Transfer Through Deep Activation Matching,
ECCV18(XVI: 611-626).
Springer DOI 1810
BibRef

Tao, Q.Y.[Qing-Yi], Yang, H.[Hao], Cai, J.F.[Jian-Fei],
Zero-Annotation Object Detection with Web Knowledge Transfer,
ECCV18(XI: 387-403).
Springer DOI 1810
BibRef

Paul, A.[Angshuman], Majumdar, A.[Angshul], Mukherjee, D.P.[Dipti Prasad],
Discriminative Autoencoder,
ICIP18(3049-3053)
IEEE DOI 1809
Minimization, Linear programming, Training, Encoding, Biomedical imaging, Decoding, Autoencoder, discriminative, cross-dataset BibRef

Inoue, T., Choudhury, S., de Magistris, G., Dasgupta, S.,
Transfer Learning from Synthetic to Real Images Using Variational Autoencoders for Precise Position Detection,
ICIP18(2725-2729)
IEEE DOI 1809
Lighting, Training, Task analysis, Robots, Decoding, Image color analysis, Cameras, deep learning, position detection, computer simulation BibRef

Liu, X., Wang, C., Hu, Y., Zeng, Z., Bai, J., Liao, G.,
Transfer Learning with Convolutional Neural Network for Early Gastric Cancer Classification on Magnifiying Narrow-Band Imaging Images,
ICIP18(1388-1392)
IEEE DOI 1809
Feature extraction, Task analysis, Cancer, Training, Sensitivity, Convolutional neural networks, convolutional neural networks (CNNs) BibRef

Bai, T., Yang, J., Chen, J., Guo, X., Huang, X., Yao, Y.,
Double-Task Deep Q-Learning with Multiple Views,
CEFR-LCV17(1050-1058)
IEEE DOI 1802
Aerospace electronics, Cameras, Robot kinematics, Robot vision systems, Training BibRef

Chang, J.H.R.[J.H. Rick], Li, C.L.[Chun-Liang], Póczos, B.[Barnabás], Kumar, B.V.K.V.[B. V. K. Vijaya],
One Network to Solve Them All: Solving Linear Inverse Problems Using Deep Projection Models,
ICCV17(5889-5898)
IEEE DOI 1802
compressed sensing, image restoration, inverse problems, iterative methods, learning (artificial intelligence), Signal resolution BibRef

Li, D., Yang, Y., Song, Y.Z., Hospedales, T.M.,
Deeper, Broader and Artier Domain Generalization,
ICCV17(5543-5551)
IEEE DOI 1802
learning (artificial intelligence), DG alternatives, DG benchmark dataset, DG methods, benchmarks, Painting BibRef

Kim, K.I.[Kwang In], Richardt, C.[Christian], Chang, H.J.[Hyung Jin],
Combining Task Predictors via Enhancing Joint Predictability,
ECCV20(XVI: 439-455).
Springer DOI 2010
BibRef

Kim, K.I.[Kwang In], Tompkin, J.[James],
Testing using Privileged Information by Adapting Features with Statistical Dependence,
ICCV21(9385-9393)
IEEE DOI 2203
Training, Visualization, Toy manufacturing industry, Training data, Feature extraction, Prediction algorithms, Machine learning architectures and formulations BibRef

Kim, K.I.[Kwang In], Tompkin, J.[James], Richardt, C.[Christian],
Predictor Combination at Test Time,
ICCV17(3573-3581)
IEEE DOI 1802
differential geometry, image denoising, learning (artificial intelligence), prediction theory, Training BibRef

Aygün, M., Aytar, Y., Ekenel, H.K.,
Exploiting Convolution Filter Patterns for Transfer Learning,
TASKCV17(2674-2680)
IEEE DOI 1802
Analytical models, Convolution, Covariance matrices, Detectors, Training BibRef

Devi, V.S.[V. Sowmini], Padmanabhan, V.[Vineet], Pujari, A.K.[Arun K.],
A Matrix Factorization & Clustering Based Approach for Transfer Learning,
PReMI17(77-83).
Springer DOI 1711
BibRef

Zhang, J., Li, W., Ogunbona, P.,
Joint Geometrical and Statistical Alignment for Visual Domain Adaptation,
CVPR17(5150-5158)
IEEE DOI 1711
Image recognition, Linear programming, Minimization, Training, Visualization BibRef

Yu, L.J.[Liang-Jiang], Fan, G.L.[Guo-Liang],
Rare Class Oriented Scene Labeling Using CNN Incorporated Label Transfer,
ISVC16(I: 309-320).
Springer DOI 1701
BibRef

Littwin, E., Wolf, L.,
Complexity of multiverse networks and their multilayer generalization,
ICPR16(372-377)
IEEE DOI 1705
Complexity theory, Feeds, Joining processes, Neural networks, Nonhomogeneous media, Training, Upper, bound BibRef

Littwin, E., Wolf, L.,
The Multiverse Loss for Robust Transfer Learning,
CVPR16(3957-3966)
IEEE DOI 1612
BibRef

Sharmanska, V., Quadrianto, N.,
Learning from the Mistakes of Others: Matching Errors in Cross-Dataset Learning,
CVPR16(3967-3975)
IEEE DOI 1612
BibRef

Heravi, E.J.[Elnaz Jahani], Aghdam, H.H.[Hamed Habibi], Puig, D.[Domenec],
Training a Mentee Network by Transferring Knowledge from a Mentor Network,
TASKCV16(III: 500-507).
Springer DOI 1611
BibRef

Yan, Y.G.[Yu-Guang], Wu, Q.Y.[Qing-Yao], Tan, M.K.[Ming-Kui], Min, H.Q.[Hua-Qing],
Online Heterogeneous Transfer Learning by Weighted Offline and Online Classifiers,
TASKCV16(III: 467-474).
Springer DOI 1611
BibRef

Sun, B., Peng, X.C.[Xing-Chao], Yu, S.X., Saenko, K.,
Ground2sky label transfer for fine-grained aerial car recognition,
ICIP17(360-364)
IEEE DOI 1803
Automobiles, Google, Image color analysis, Image recognition, Image resolution, Object recognition, Task analysis, Label Transfer BibRef

Peng, X.C.[Xing-Chao], Hoffman, J., Yu, S.X., Saenko, K.[Kate],
Fine-to-coarse knowledge transfer for low-res image classification,
ICIP16(3683-3687)
IEEE DOI 1610
Automobiles BibRef

Irie, G.[Go], Arai, H.[Hiroyuki], Taniguchi, Y.[Yukinobu],
Alternating Co-Quantization for Cross-Modal Hashing,
ICCV15(1886-1894)
IEEE DOI 1602
Binary codes BibRef

Shkodrani, S.[Sindi], Hofmann, M.[Michael], Gavves, E.[Efstratios],
Dynamic Adaptation on Non-stationary Visual Domains,
TASKCV18(II:158-171).
Springer DOI 1905
BibRef

Gavves, E., Mensink, T., Tommasi, T., Snoek, C.G.M., Tuytelaars, T.,
Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks,
ICCV15(2731-2739)
IEEE DOI 1602
Computer vision BibRef

Paul, A., Rottensteiner, F., Heipke, C.,
Transfer Learning Based on Logistic Regression,
CMRT15(145-152).
DOI Link 1602
BibRef

Liu, P.C.[Peng-Cheng], Wang, C.[Chong], Yang, P.P.[Pei-Pei], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Cross-Domain Object Recognition Using Object Alignment,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Rochan, M.[Mrigank], Wang, Y.[Yang],
Weakly supervised localization of novel objects using appearance transfer,
CVPR15(4315-4324)
IEEE DOI 1510
BibRef

Dai, D.X.[Deng-Xin], Kroeger, T.[Till], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Metric imitation by manifold transfer for efficient vision applications,
CVPR15(3527-3536)
IEEE DOI 1510
BibRef

Niu, L.[Li], Li, W.[Wen], Xu, D.[Dong],
Visual recognition by learning from web data: A weakly supervised domain generalization approach,
CVPR15(2774-2783)
IEEE DOI 1510
BibRef

Isola, P.[Phillip], Lim, J.J.[Joseph J.], Adelson, E.H.[Edward H.],
Discovering states and transformations in image collections,
CVPR15(1383-1391)
IEEE DOI 1510
BibRef

Royer, A.[Amelie], Lampert, C.H.[Christoph H.],
Classifier adaptation at prediction time,
CVPR15(1401-1409)
IEEE DOI 1510
BibRef

Lu, Y.[Ying], Chen, L.M.[Li-Ming], Saidi, A.[Alexandre], Zhang, Z.X.[Zhao-Xiang], Wang, Y.H.[Yun-Hong],
Learning visual categories through a sparse representation classifier based cross-category knowledge transfer,
ICIP14(165-169)
IEEE DOI 1502
Computer vision BibRef

Kim, J.[Jongdae], Collomosse, J.P.[John P.],
Incremental transfer learning for object recognition in streaming video,
ICIP14(2729-2733)
IEEE DOI 1502
Kernel BibRef

Wang, Z.H.[Zi-Heng], Gao, T.[Tian], Ji, Q.A.[Qi-Ang],
Learning with Hidden Information Using a Max-Margin Latent Variable Model,
ICPR14(1389-1394)
IEEE DOI 1412
Data models BibRef

Zhou, Y.[Yun], Ioannou, I.[Ioanna], Wijewickrema, S.[Sudanthi], Bailey, J.[James], Piromchai, P.[Patorn], Kennedy, G.[Gregor], OLeary, S.[Stephen],
Transfer Learning of a Temporal Bone Performance Model via Anatomical Feature Registration,
ICPR14(1916-1921)
IEEE DOI 1412
Adaptation models BibRef

Fang, Z.[Zheng], Zhang, Z.F.[Zhong-Fei],
Cross Domain Shared Subspace Learning for Unsupervised Transfer Classification,
ICPR14(3927-3932)
IEEE DOI 1412
Accuracy BibRef

Samanta, S.[Suranjana], Selvan, T.[Tirumarai], Das, S.[Sukhendu],
Modeling Sequential Domain Shift through Estimation of Optimal Sub-spaces for Categorization,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Farajidavar, N.[Nazli], de Campos, T.[Teofilo], Kittler, J.V.[Josef V.],
Transductive Transfer Machine,
ACCV14(III: 623-639).
Springer DOI 1504
BibRef
And:
Adaptive Transductive Transfer Machine,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Amaral, T.[Telmo], Silva, L.M.[Luís M.], Alexandre, L.A.[Luís A.], Kandaswamy, C.[Chetak], de Sá, J.M.[Joaquim Marques], Santos, J.M.[Jorge M.],
Transfer Learning Using Rotated Image Data to Improve Deep Neural Network Performance,
ICIAR14(I: 290-300).
Springer DOI 1410
BibRef

Branson, S.[Steve], Hjorleifsson, K.E.[Kristjan Eldjarn], Perona, P.[Pietro],
Active Annotation Translation,
CVPR14(3702-3709)
IEEE DOI 1409
active learning. Quickly annotate when previous annotations exist. BibRef

Zhang, B.[Bang], Wang, Y.[Yi], Wang, Y.[Yang], Chen, F.[Fang],
Stable Learning in Coding Space for Multi-class Decoding and Its Extension for Multi-class Hypothesis Transfer Learning,
CVPR14(1075-1081)
IEEE DOI 1409
Multi-class classification; output coding framework; transfer learning BibRef

Tsuchiya, M., Yamauchi, Y., Fujiyoshi, H., Yamashita, T.,
Hybrid Transfer Learning for Efficient Learning in Object Detection,
ACPR13(69-73)
IEEE DOI 1408
feature extraction BibRef

Rana, A.[Aakanksha], Zepeda, J.[Joaquin], Perez, P.[Patrick],
Feature Learning for the Image Retrieval Task,
FSLCV14(III: 152-165).
Springer DOI 1504
BibRef

Kulkarni, P.[Praveen], Zepeda, J.[Joaquin], Jurie, F.[Frederic], Pérez, P.[Patrick], Chevallier, L.[Louis],
Learning the Structure of Deep Architectures Using L1 Regularization,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Kulkarni, P.[Praveen], Sharma, G.[Gaurav], Zepeda, J.[Joaquin], Chevallier, L.[Louis],
Transfer learning via attributes for improved on-the-fly classification,
WACV14(220-226)
IEEE DOI 1406
Animals BibRef

Long, M.S.[Ming-Sheng], Ding, G.G.[Gui-Guang], Wang, J.M.[Jian-Min], Sun, J.G.[Jia-Guang], Guo, Y.C.[Yu-Chen], Yu, P.S.[Philip S.],
Transfer Sparse Coding for Robust Image Representation,
CVPR13(407-414)
IEEE DOI 1309
image representation; sparse coding; transfer learning BibRef

Kobetski, M.[Miroslav], Sullivan, J.[Josephine],
Discriminative tree-based feature mapping,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Kobetski, M.[Miroslav], Sullivan, J.[Josephine],
Apprenticeship Learning: Transfer of Knowledge via Dataset Augmentation,
SCIA13(432-443).
Springer DOI 1311
BibRef

Chen, S.K.[Shao-Kang], Sanderson, C.[Conrad], Harandi, M.T.[Mehrtash T.], Lovell, B.C.[Brian C.],
Improved Image Set Classification via Joint Sparse Approximated Nearest Subspaces,
CVPR13(452-459)
IEEE DOI 1309
Adaptive Clustering BibRef

Kuzborskij, I.[Ilja], Orabona, F.[Francesco], Caputo, B.[Barbara],
Transfer Learning Through Greedy Subset Selection,
CIAP15(I:3-14).
Springer DOI 1511
BibRef
Earlier:
From N to N+1: Multiclass Transfer Incremental Learning,
CVPR13(3358-3365)
IEEE DOI 1309
LSSVM BibRef

Sharmanska, V.[Viktoriia], Quadrianto, N.[Novi], Lampert, C.H.[Christoph H.],
Learning to Rank Using Privileged Information,
ICCV13(825-832)
IEEE DOI 1403
Learning to rank with more data in training than in test. BibRef

Liu, J.C.[Jing-Chen], McCloskey, S.[Scott], Liu, Y.X.[Yan-Xi],
Training data recycling for multi-level learning,
ICPR12(2314-2318).
WWW Link. 1302
BibRef

Costa Pereira, J.[Jose], Vasconcelos, N.M.[Nuno M.],
On the regularization of image semantics by modal expansion,
CVPR12(3093-3099).
IEEE DOI 1208
BibRef

Guillaumin, M.[Matthieu], Ferrari, V.[Vittorio],
Large-scale knowledge transfer for object localization in ImageNet,
CVPR12(3202-3209).
IEEE DOI 1208
BibRef

Ye, G.N.[Guang-Nan], Liu, D.[Dong], Jhuo, I.H.[I-Hong], Chang, S.F.[Shih-Fu],
Robust late fusion with rank minimization,
CVPR12(3021-3028).
IEEE DOI 1208
BibRef

Aytar, Y.[Yusuf], Zisserman, A.[Andrew],
Tabula rasa: Model transfer for object category detection,
ICCV11(2252-2259).
IEEE DOI 1201
Transfer learning for categories. BibRef

Wang, H.[Hua], Nie, F.P.[Fei-Ping], Huang, H.[Heng], Ding, C.[Chris],
Dyadic transfer learning for cross-domain image classification,
ICCV11(551-556).
IEEE DOI 1201
BibRef

Yu, X.D.[Xiao-Dong], Aloimonos, Y.F.[Yi-Fannis],
Attribute-Based Transfer Learning for Object Categorization with Zero/One Training Example,
ECCV10(V: 127-140).
Springer DOI 1009
BibRef

Yao, Y.[Yi], Doretto, G.[Gianfranco],
Boosting for transfer learning with multiple sources,
CVPR10(1855-1862).
IEEE DOI 1006
Transfer info between domains. BibRef

Lampert, C.H.[Christoph H.], Krömer, O.[Oliver],
Weakly-Paired Maximum Covariance Analysis for Multimodal Dimensionality Reduction and Transfer Learning,
ECCV10(II: 566-579).
Springer DOI 1009
BibRef

Ahmed, A.[Amr], Yu, K.[Kai], Xu, W.[Wei], Gong, Y.H.[Yi-Hong], Xing, E.[Eric],
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks,
ECCV08(III: 69-82).
Springer DOI 0810
BibRef

Quattoni, A.[Ariadna], Collins, M.[Michael], Darrell, T.J.[Trevor J.],
Transfer learning for image classification with sparse prototype representations,
CVPR08(1-8).
IEEE DOI 0806
BibRef
And: CSAIL-2008-012, March 2008.
WWW Link. BibRef
Earlier:
Learning Visual Representations using Images with Captions,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Pre-Training .