14.1.5 Transfer Learning from Other Tasks, Other Classes

Chapter Contents (Back)
Transfer Learning.
See also Multi-Task Learning, Multiple Tasks, Transfer Learning, Domain Adaption. A lot of similarity to Domain Adaption:
See also Domain Adaptation.
See also Adversarial Networks for Transfer Learning, Domain Adaption.
See also Knowledge Distillation.

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.[Xiaowu], Song, Y.[Yafei], 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

Shoeleh, F.[Farzaneh], Asadpour, M.[Masoud],
Graph based skill acquisition and transfer Learning for continuous reinforcement learning domains,
PRL(87), No. 1, 2017, pp. 104-116.
Elsevier DOI 1703
Reinforcement learning BibRef

Wang, J.[Jie], Luo, C.[Chang], Huang, H.Q.[Han-Qiao], Zhao, H.Z.[Hui-Zhen], Wang, S.Q.[Shi-Qiang],
Transferring Pre-Trained Deep CNNs for Remote Scene Classification with General Features Learned from Linear PCA Network,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
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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
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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
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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
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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, Pattern recognition, 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

Basavaraju, S.[Sathisha], Gaj, S.[Sibaji], Sur, A.[Arijit],
Object Memorability Prediction using Deep Learning: Location and Size Bias,
JVCIR(59), 2019, pp. 117-127.
Elsevier DOI 1903
Object Memorability, Deep Learning, Transfer Learning BibRef

Ye, R.[Rui], Dai, Q.[Qun], Li, M.[MeiLing],
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
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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
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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
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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
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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.[Lingkun], 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
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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

Wen, Y.[Yang], Chen, L.T.[Lei-Ting], Deng, Y.[Yu], Zhou, C.[Chuan],
Rethinking pre-training on medical imaging,
JVCIR(78), 2021, pp. 103145.
Elsevier DOI 2107
Transfer learning, Medical image analysis, Convolutional neural network, Survival prediction BibRef

Liu, T.H.[Tai-Heng], Deng, X.Q.[Xiu-Qin], He, Z.S.[Zhao-Shui], Long, Y.H.[Yong-Hong],
TCD-CF: Triple cross-domain collaborative filtering recommendation,
PRL(149), 2021, pp. 185-192.
Elsevier DOI 2108
Cross-domain collaborative filtering, Transfer learning, Data sparsity, Co-clustering BibRef

García-Ramírez, J.[Jesús], Morales, E.[Eduardo], Escalante, H.J.[Hugo Jair],
Multi-source Transfer Learning for Deep Reinforcement Learning,
MCPR21(131-140).
Springer DOI 2108
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Azzam, M.[Mohamed], Wu, W.H.[Wen-Hao], Cao, W.[Wenming], 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

Hwang, R.[Rakhoon], Lee, H.J.[Han-Jin], Hwang, H.J.[Hyung Ju],
Option compatible reward inverse reinforcement learning,
PRL(154), 2022, pp. 83-89.
Elsevier DOI 2202
Reinforcement learning, Inverse reinforcement learning, Transfer learning, Machine learning 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

Nicholaus, I.T.[Isack Thomas], Kang, D.K.[Dae-Ki],
Robust experience replay sampling for multi-agent reinforcement learning,
PRL(155), 2022, pp. 135-142.
Elsevier DOI 2203
Reinforcement learning, Multi-agent, Sampling, Experience replay 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

Guo, S.Q.[Shang-Qi], Yan, Q.[Qi], Su, X.[Xin], Hu, X.L.[Xiao-Lin], Chen, F.[Feng],
State-Temporal Compression in Reinforcement Learning With the Reward-Restricted Geodesic Metric,
PAMI(44), No. 9, September 2022, pp. 5572-5589.
IEEE DOI 2208
Measurement, Task analysis, Reinforcement learning, Neural networks, Time-domain analysis, reinforcement learning (RL) 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

Xu, T.[Tian], Li, Z.N.[Zi-Niu], Yu, Y.[Yang],
Error Bounds of Imitating Policies and Environments for Reinforcement Learning,
PAMI(44), No. 10, October 2022, pp. 6968-6980.
IEEE DOI 2209
Planning, Reinforcement learning, Cloning, Complexity theory, Supervised learning, Decision making, Upper bound, model-based reinforcement learning 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

Zhang, T.[Tong], Gao, P.[Peng], Dong, H.[Hao], Zhuang, Y.[Yin], Wang, G.Q.[Guan-Qun], Zhang, W.[Wei], Chen, H.[He],
Consecutive Pre-Training: A Knowledge Transfer Learning Strategy with Relevant Unlabeled Data for Remote Sensing Domain,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
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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

Wei, L.[Longhui], Xie, L.X.[Ling-Xi], Zhou, W.G.[Wen-Gang], Li, H.Q.[Hou-Qiang], Tian, Q.[Qi],
MVP: Multimodality-Guided Visual Pre-training,
ECCV22(XXX:337-353).
Springer DOI 2211
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.[Borui], Song, R.J.[Ren-Jie], Zhou, B.[Boyan], Liang, J.J.[Jia-Jun], Yoshie, O.[Osamu],
Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective,
ECCV22(XXVI:20-37).
Springer DOI 2211
BibRef

Yuan, Z.W.[Zhuo-Wen], Wu, F.[Fan], Long, Y.H.[Yun-Hui], Xiao, C.W.[Chao-Wei], Li, B.[Bo],
SecretGen: Privacy Recovery on Pre-trained Models via Distribution Discrimination,
ECCV22(V:139-155).
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.[Ziyu], 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, Pattern recognition, Task analysis, Vision+language, Transfer/low-shot/long-tail learning BibRef

Chakraborty, S.[Shuvam], Uzkent, B.[Burak], Ayush, K.[Kumar], Tanmay, K.[Kumar], Sheehan, E.[Evan], Ermon, S.[Stefano],
Efficient Conditional Pre-training for Transfer Learning,
L3D-IVU22(4240-4249)
IEEE DOI 2210
Training, Costs, Image resolution, Filtering, Computational modeling, Transfer 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

Li, Z.W.[Zhao-Wen], Zhu, Y.S.[You-Song], Yang, F.[Fan], Li, W.[Wei], Zhao, C.Y.[Chao-Yang], Chen, Y.Y.[Ying-Ying], Chen, Z.Y.[Zhi-Yang], Xie, J.H.[Jia-Hao], Wu, L.[Liwei], Zhao, R.[Rui], Tang, M.[Ming], Wang, J.Q.[Jin-Qiao],
UniVIP: A Unified Framework for Self-Supervised Visual Pre-training,
CVPR22(14607-14616)
IEEE DOI 2210
Representation learning, Visualization, Image segmentation, Correlation, Semantics, Self-supervised learning, Object detection, Transfer/low-shot/long-tail 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, Pattern recognition, 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, Pattern recognition, 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, Pattern recognition, 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

Mishra, S.[Samarth], Panda, R.[Rameswar], Phoo, C.P.[Cheng Perng], Chen, C.F.R.[Chun-Fu Richard], Karlinsky, L.[Leonid], Saenko, K.[Kate], Saligrama, V.[Venkatesh], Feris, R.S.[Rogerio S.],
Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data,
CVPR22(9184-9194)
IEEE DOI 2210
Graphics, Training, Representation learning, Adaptation models, Computational modeling, Data models, retrieval 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

Singh, M.[Mannat], Gustafson, L.[Laura], Adcock, A.[Aaron], de Freitas-Reis, V.[Vinicius], Gedik, B.[Bugra], Kosaraju, R.P.[Raj Prateek], Mahajan, D.[Dhruv], Girshick, R.[Ross], Dollár, P.[Piotr], van der Maaten, L.[Laurens],
Revisiting Weakly Supervised Pre-Training of Visual Perception Models,
CVPR22(794-804)
IEEE DOI 2210
Visualization, Computational modeling, Supervised learning, Self-supervised learning, Pattern recognition, Standards, Transfer/low-shot/long-tail learning 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

Mañas, O.[Oscar], Lacoste, A.[Alexandre], Giró-i-Nieto, X.[Xavier], Vazquez, D.[David], Rodríguez, P.[Pau],
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data,
ICCV21(9394-9403)
IEEE DOI 2203
Earth, Deep learning, Satellites, Transfer learning, Pipelines, Supervised learning, Data models, Vision applications and systems 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

Kim, B.[Beomyoung], Yoo, Y.J.[Young-Joon], Rhee, C.E.[Chae Eun], Kim, J.[Junmo],
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-Refinement,
CVPR22(4268-4277)
IEEE DOI 2210
Training, Location awareness, Image segmentation, Shape, Semantics, Pattern recognition, Proposals, Segmentation, Self- semi- meta- unsupervised learning BibRef

Hong, S.[Seungbum], Yoon, J.[Jihun], Choi, M.K.[Min-Kook], Kim, J.[Junmo],
Self-Supervised Knowledge Transfer via Loosely Supervised Auxiliary Tasks,
WACV22(2947-2956)
IEEE DOI 2202
Training, Knowledge engineering, Codes, Transfer learning, Heterogeneous networks, Semi- and Un- supervised Learning BibRef

Suzuki, S.[Satoshi], Takeda, S.[Shoichiro], Tanida, R.[Ryuichi], Kimata, H.[Hideaki], Shouno, H.[Hayaru],
Knowledge Transferred Fine-Tuning for Anti-Aliased Convolutional Neural Network in Data-Limited Situation,
ICIP21(864-868)
IEEE DOI 2201
Knowledge engineering, Training, Image recognition, Training data, Convolutional neural networks, Knowledge transfer, data-limited situation 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

Abuduweili, A.[Abulikemu], Li, X.J.[Xing-Jian], Shi, H.[Humphrey], Xu, C.Z.[Cheng-Zhong], Dou, D.J.[De-Jing],
Adaptive Consistency Regularization for Semi-Supervised Transfer Learning,
CVPR21(6919-6928)
IEEE DOI 2111
Adaptation models, Codes, Transfer learning, Supervised learning, Semisupervised learning, Benchmark testing 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

Jamal, M.A.[Muhammad Abdullah], Wang, L.Q.[Li-Qiang], Gong, B.Q.[Bo-Qing],
A Lazy Approach to Long-Horizon Gradient-Based Meta-Learning,
ICCV21(6557-6566)
IEEE DOI 2203
Computational modeling, Space exploration, Object recognition, Task analysis, Optimization and learning methods, Efficient training and inference methods 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, Pattern recognition, 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

Zhu, L.C.[Lin-Chao], Arik, S.Ö.[Sercan Ö.], Yang, Y.[Yi], Pfister, T.[Tomas],
Learning to Transfer Learn: Reinforcement Learning-based Selection for Adaptive Transfer Learning,
ECCV20(XXVII:342-358).
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

Yan, X.T.[Xue-Ting], Misra, I.[Ishan], Gupta, A.[Abhinav], Ghadiyaram, D.[Deepti], Mahajan, D.[Dhruv],
ClusterFit: Improving Generalization of Visual Representations,
CVPR20(6508-6517)
IEEE DOI 2008
Pre-training. Task analysis, Training, Feature extraction, Visualization, Videos, Tagging, Twitter 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)
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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,
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Jakubovitz, D., Rodrigues, M.R.D., Giryes, R.,
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SDL-CV19(763-767)
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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],
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CVPR19(12379-12388).
IEEE DOI 2002
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CVPR19(11285-11294).
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Chen, Y.C.[Yun-Chun], Lin, Y.Y.[Yen-Yu], Yang, M.H.[Ming-Hsuan], Huang, J.B.[Jia-Bin],
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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

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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

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GCPR18(228-243).
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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
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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)
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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.,
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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).
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Huang, H.S.[Hao-Shuo], Huang, Q.X.[Qi-Xing], Krähenbühl, P.[Philipp],
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ECCV18(XVI: 611-626).
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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).
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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

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Combining Task Predictors via Enhancing Joint Predictability,
ECCV20(XVI: 439-455).
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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).
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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, Pattern recognition, Training, Visualization BibRef

Ge, W., Yu, Y.,
Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-Tuning,
CVPR17(10-19)
IEEE DOI 1711
Kernel, Machine learning, Neural networks, Training data, 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
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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
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Sharmanska, V., Quadrianto, N.,
Learning from the Mistakes of Others: Matching Errors in Cross-Dataset Learning,
CVPR16(3967-3975)
IEEE DOI 1612
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Chu, B.[Brian], Madhavan, V.[Vashisht], Beijbom, O.[Oscar], Hoffman, J.[Judy], Darrell, T.J.[Trevor J.],
Best Practices for Fine-Tuning Visual Classifiers to New Domains,
TASKCV16(III: 435-442).
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Heravi, E.J.[Elnaz Jahani], Aghdam, H.H.[Hamed Habibi], Puig, D.[Domenec],
Training a Mentee Network by Transferring Knowledge from a Mentor Network,
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Springer DOI 1611
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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).
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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

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Dynamic Adaptation on Non-stationary Visual Domains,
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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).
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Cross-Domain Object Recognition Using Object Alignment,
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Weakly supervised localization of novel objects using appearance transfer,
CVPR15(4315-4324)
IEEE DOI 1510
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Metric imitation by manifold transfer for efficient vision applications,
CVPR15(3527-3536)
IEEE DOI 1510
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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
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Discovering states and transformations in image collections,
CVPR15(1383-1391)
IEEE DOI 1510
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Classifier adaptation at prediction time,
CVPR15(1401-1409)
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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)
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Computer vision BibRef

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

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Transfer Learning of a Temporal Bone Performance Model via Anatomical Feature Registration,
ICPR14(1916-1921)
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ICPR14(3927-3932)
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CVPR14(3702-3709)
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Stable Learning in Coding Space for Multi-class Decoding and Its Extension for Multi-class Hypothesis Transfer Learning,
CVPR14(1075-1081)
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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)
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Rana, A.[Aakanksha], Zepeda, J.[Joaquin], Perez, P.[Patrick],
Feature Learning for the Image Retrieval Task,
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BMVC15(xx-yy).
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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,
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Kobetski, M.[Miroslav], Sullivan, J.[Josephine],
Apprenticeship Learning: Transfer of Knowledge via Dataset Augmentation,
SCIA13(432-443).
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Qualitative Transfer for Reinforcement Learning with Continuous State and Action Spaces,
CIARP13(I:198-205).
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Improved Image Set Classification via Joint Sparse Approximated Nearest Subspaces,
CVPR13(452-459)
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Adaptive Clustering BibRef

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Transfer Learning Through Greedy Subset Selection,
CIAP15(I:3-14).
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Earlier:
From N to N+1: Multiclass Transfer Incremental Learning,
CVPR13(3358-3365)
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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
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Training data recycling for multi-level learning,
ICPR12(2314-2318).
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On the regularization of image semantics by modal expansion,
CVPR12(3093-3099).
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Guillaumin, M.[Matthieu], Ferrari, V.[Vittorio],
Large-scale knowledge transfer for object localization in ImageNet,
CVPR12(3202-3209).
IEEE DOI 1208
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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
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Aytar, Y.[Yusuf], Zisserman, A.[Andrew],
Tabula rasa: Model transfer for object category detection,
ICCV11(2252-2259).
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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
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Yu, X.D.[Xiao-Dong], Aloimonos, Y.[Yiannis],
Attribute-Based Transfer Learning for Object Categorization with Zero/One Training Example,
ECCV10(V: 127-140).
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Yao, Y.[Yi], Doretto, G.[Gianfranco],
Boosting for transfer learning with multiple sources,
CVPR10(1855-1862).
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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
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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).
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Transfer learning for image classification with sparse prototype representations,
CVPR08(1-8).
IEEE DOI 0806
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Earlier:
Learning Visual Representations using Images with Captions,
CVPR07(1-8).
IEEE DOI 0706
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Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Domain Adaptation .


Last update:Dec 4, 2022 at 15:58:45