14.5.5 Self-Supervised Learning

Chapter Contents (Back)
Self-Supervised. Learning.
See also Self-Supervised Learning for Object Detection and Segmentation.

You, C.[Chong], Li, C.[Chi], Robinson, D.P.[Daniel P.], Vidal, R.[René],
Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces,
PAMI(44), No. 5, May 2022, pp. 2698-2711.
IEEE DOI 2204
Clustering algorithms, Data models, Databases, Clustering methods, Optimization, Image reconstruction, subspace clustering BibRef

Shi, W.J.[Wen-Jie], Huang, G.[Gao], Song, S.[Shiji], Wang, Z.Y.[Zhuo-Yuan], Lin, T.Y.[Ting-Yu], Wu, C.[Cheng],
Self-Supervised Discovering of Interpretable Features for Reinforcement Learning,
PAMI(44), No. 5, May 2022, pp. 2712-2724.
IEEE DOI 2204
Task analysis, Decision making, Perturbation methods, Reinforcement learning, Jacobian matrices, Visualization, Games, decision-making process BibRef

Shi, W.J.[Wen-Jie], Huang, G.[Gao], Song, S.[Shiji], Wu, C.[Cheng],
Temporal-Spatial Causal Interpretations for Vision-Based Reinforcement Learning,
PAMI(44), No. 12, December 2022, pp. 10222-10235.
IEEE DOI 2212
Adaptation models, Reliability, Decision making, Perturbation methods, Visualization, Task analysis, temporal causality BibRef

Durrant, A.[Aiden], Leontidis, G.[Georgios],
Hyperspherically regularized networks for self-supervision,
IVC(124), 2022, pp. 104494.
Elsevier DOI 2208
Self-supervised learning, Representation learning, Representation separability, Image classification BibRef

Berg, P.[Paul], Pham, M.T.[Minh-Tan], Courty, N.[Nicolas],
Self-Supervised Learning for Scene Classification in Remote Sensing: Current State of the Art and Perspectives,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Gao, Y.[Yuan], Sun, X.J.[Xiao-Juan], Liu, C.[Chao],
A General Self-Supervised Framework for Remote Sensing Image Classification,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Chen, X.L.[Xi-Liang], Zhu, G.B.[Guo-Bin], Liu, M.Q.[Ming-Qing],
Remote Sensing Image Scene Classification with Self-Supervised Learning Based on Partially Unlabeled Datasets,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Calhoun, Z.D.[Zachary D.], Lahrichi, S.[Saad], Ren, S.[Simiao], Malof, J.M.[Jordan M.], Bradbury, K.[Kyle],
Self-Supervised Encoders Are Better Transfer Learners in Remote Sensing Applications,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Li, S.[Shuo], Liu, F.[Fang], Hao, Z.[Zehua], Jiao, L.C.[Li-Cheng], Liu, X.[Xu], Guo, Y.W.[Yu-Wei],
MinEnt: Minimum entropy for self-supervised representation learning,
PR(138), 2023, pp. 109364.
Elsevier DOI 2303
Self-supervised learning, Minimum entropy, Unsupervised representation learning, Image classification BibRef

Wang, H.[Hanxuan], Lu, N.[Na], Luo, H.[Huan], Liu, Q.[Qinyang],
Self-supervised clustering with assistance from off-the-shelf classifier,
PR(138), 2023, pp. 109350.
Elsevier DOI 2303
Deep clustering, Classification, Self-supervised, Sample selection BibRef

Cheng, H.Y.[Hao-Yang], Li, H.L.[Hong-Liang], Qiu, H.Q.[He-Qian], Wu, Q.[Qingbo], Zhang, X.L.[Xiao-Liang], Meng, F.[Fanman], Ngan, K.N.[King Ngi],
Unsupervised Visual Representation Learning via Multi-Dimensional Relationship Alignment,
IP(32), 2023, pp. 1613-1626.
IEEE DOI 2303
Task analysis, Self-supervised learning, Image reconstruction, Optimization, Visualization, Training, Representation learning, convolutional neural network BibRef

Alfaro-Contreras, M.[María], Ríos-Vila, A.[Antonio], Valero-Mas, J.J.[Jose J.], Calvo-Zaragoza, J.[Jorge],
Few-shot symbol classification via self-supervised learning and nearest neighbor,
PRL(167), 2023, pp. 1-8.
Elsevier DOI 2303
Symbol classification, Document image analysis, Self-Supervised learning, Few-Shot classification BibRef

Qin, Y.[Yao], Ye, Y.X.[Yuan-Xin], Zhao, Y.[Yue], Wu, J.Z.[Jun-Zheng], Zhang, H.[Han], Cheng, K.[Kenan], Li, K.[Kun],
Nearest Neighboring Self-Supervised Learning for Hyperspectral Image Classification,
RS(15), No. 6, 2023, pp. 1713.
DOI Link 2304
BibRef

Ye, F.[Fei], Bors, A.G.[Adrian G.],
Dynamic Self-Supervised Teacher-Student Network Learning,
PAMI(45), No. 5, May 2023, pp. 5731-5748.
IEEE DOI 2304
Task analysis, Mixture models, Training, Generative adversarial networks, Data models, teacher-student framework BibRef

Wei, L.H.[Long-Hui], Xie, L.X.[Ling-Xi], Zhou, W.G.[Wen-Gang], Li, H.Q.[Hou-Qiang], Tian, Q.[Qi],
Exploring the diversity and invariance in yourself for visual pre-training task,
PR(139), 2023, pp. 109437.
Elsevier DOI 2304
Visual pre-training, Self-supervised learning, Multi-grained visual information BibRef

Wang, J.[Jiatai], Xu, Z.W.[Zhi-Wei], Yang, X.[Xuewen], Guo, D.J.[Dong-Jin], Liu, L.M.[Li-Min],
Self-supervised image clustering from multiple incomplete views via constrastive complementary generation,
IET-CV(17), No. 2, 2023, pp. 189-202.
DOI Link 2304
clustering from multiple incomplete views, computer vision, constrastive learning, generative adversarial network BibRef

Wang, F.[Feng], Kong, T.[Tao], Zhang, R.[Rufeng], Liu, H.P.[Hua-Ping], Li, H.[Hang],
Self-Supervised Learning by Estimating Twin Class Distribution,
IP(32), 2023, pp. 2228-2236.
IEEE DOI 2305
Task analysis, Mutual information, Entropy, Probability distribution, Self-supervised learning, image classification BibRef

Zhao, W.[Wenyi], Li, C.Y.[Chong-Yi], Zhang, W.D.[Wei-Dong], Yang, L.[Lu], Zhuang, P.X.[Pei-Xian], Li, L.Q.[Ling-Qiao], Fan, K.[Kefeng], Yang, H.H.[Hui-Hua],
Embedding Global Contrastive and Local Location in Self-Supervised Learning,
CirSysVideo(33), No. 5, May 2023, pp. 2275-2289.
IEEE DOI 2305
Task analysis, Optimization, Feature extraction, Semantics, Training, Ensemble learning, Data models, ensemble learning BibRef


Lialin, V.[Vladislav], Rawls, S.[Stephen], Chan, D.[David], Ghosh, S.[Shalini], Rumshisky, A.[Anna], Hamza, W.[Wael],
Scalable and Accurate Self-supervised Multimodal Representation Learning without Aligned Video and Text Data,
Pretrain23(390-400)
IEEE DOI 2302
Training, Representation learning, Adaptation models, Visualization, Neural networks, Optimized production technology BibRef

Yan, X.Y.[Xiang-Yi], Naushad, J.[Junayed], Sun, S.L.[Shan-Lin], Han, K.[Kun], Tang, H.[Hao], Kong, D.Y.[De-Ying], Ma, H.Y.[Hao-Yu], You, C.[Chenyu], Xie, X.H.[Xiao-Hui],
Representation Recovering for Self-Supervised Pre-training on Medical Images,
WACV23(2684-2694)
IEEE DOI 2302
Representation learning, Visualization, Image segmentation, Semantics, Self-supervised learning, Feature extraction BibRef

Sinha, S.[Samarth], Gehler, P.[Peter], Locatello, F.[Francesco], Schiele, B.[Bernt],
TeST: Test-time Self-Training under Distribution Shift,
WACV23(2758-2768)
IEEE DOI 2302
Training, Adaptation models, Image segmentation, Neural networks, Object detection, Predictive models, Prediction algorithms, visual reasoning BibRef

Mohamadi, S.[Salman], Doretto, G.[Gianfranco], Adjeroh, D.A.[Donald A.],
FUSSL: Fuzzy Uncertain Self Supervised Learning,
WACV23(2798-2807)
IEEE DOI 2302
Training, Representation learning, Protocols, Uncertainty, Annotations, Redundancy, Self-supervised learning, visual reasoning BibRef

Koçyigit, M.T.[Mustafa Taha], Hospedales, T.M.[Timothy M.], Bilen, H.[Hakan],
Accelerating Self-Supervised Learning via Efficient Training Strategies,
WACV23(5643-5653)
IEEE DOI 2302
Training, Schedules, Visualization, Costs, Self-supervised learning, Transformers, Algorithms: Machine learning architectures, visual reasoning BibRef

Chen, Z.[Zekai], Agarwal, D.[Devansh], Aggarwal, K.[Kshitij], Safta, W.[Wiem], Balan, M.M.[Mariann Micsinai], Brown, K.[Kevin],
Masked Image Modeling Advances 3D Medical Image Analysis,
WACV23(1969-1979)
IEEE DOI 2302

WWW Link. Training, Solid modeling, Analytical models, Image segmentation, Self-supervised learning, Predictive models. BibRef

Yang, H.Y.[Hua-Yi], Wang, D.Q.[De-Qing], Zhao, Z.Y.[Zheng-Yang], Wang, X.[Xuying],
SSL-DC: Improving Transduxctive Few-Shot Learning via Self-Supervised Learning and Distribution Calibration,
ICPR22(4892-4898)
IEEE DOI 2212
Training, Art, Prototypes, Self-supervised learning, Gaussian distribution, Generative adversarial networks, Calibration BibRef

Huang, Y.H.[Yue-Hong], Tseng, Y.C.[Yu-Chee],
A Self-Supervised Solution for the Switch-Toggling Visual Task,
ICPR22(3429-3435)
IEEE DOI 2212
Training, Visualization, Switches, Self-supervised learning, Reinforcement learning, Cognition BibRef

Liu, H.T.[Hao-Tian], Cai, M.[Mu], Lee, Y.J.[Yong Jae],
Masked Discrimination for Self-supervised Learning on Point Clouds,
ECCV22(II:657-675).
Springer DOI 2211
BibRef

Thoker, F.M.[Fida Mohammad], Doughty, H.[Hazel], Bagad, P.[Piyush], Snoek, C.G.M.[Cees G.M.],
How Severe Is Benchmark-Sensitivity in Video Self-Supervised Learning?,
ECCV22(XXXIV:632-652).
Springer DOI 2211

WWW Link. Analyze self-supervised learning. BibRef

Prabhu, S.M.[Sahana M.], Katta, J.Y.[Jitendra Y.], Kale, A.A.[Amit A.],
Self-Supervised Learning for Texture Classification Using Limited Labeled Data,
ICIP22(1416-1420)
IEEE DOI 2211
Representation learning, Visualization, Training data, Self-supervised learning, Performance gain, Data models BibRef

Amrani, E.[Elad], Karlinsky, L.[Leonid], Bronstein, A.[Alex],
Self-Supervised Classification Network,
ECCV22(XXXI:116-132).
Springer DOI 2211
BibRef

Moon, W.J.[Won-Jun], Kim, J.H.[Ji-Hwan], Heo, J.P.[Jae-Pil],
Tailoring Self-Supervision for Supervised Learning,
ECCV22(XXV:346-364).
Springer DOI 2211
BibRef

Mu, N.[Norman], Kirillov, A.[Alexander], Wagner, D.[David], Xie, S.[Saining],
SLIP: Self-supervision Meets Language-Image Pre-training,
ECCV22(XXVI:529-544).
Springer DOI 2211
BibRef

Quan, Y.H.[Yu-Hui], Qin, X.R.[Xin-Ran], Pang, T.Y.[Tong-Yao], Ji, H.[Hui],
Dual-Domain Self-supervised Learning and Model Adaption for Deep Compressive Imaging,
ECCV22(XXX:409-426).
Springer DOI 2211
BibRef

Peri, R.[Raghuveer], Parthasarathy, S.[Srinivas], Sundaram, S.[Shiva],
Scene Representation Learning from Videos Using Self-Supervised and Weakly-Supervised Techniques,
ICIP22(1671-1675)
IEEE DOI 2211
Training, Representation learning, Image analysis, Image recognition, Filtering, Image representation, self-supervised BibRef

Addepalli, S.[Sravanti], Bhogale, K.[Kaushal], Dey, P.[Priyam], Babu, R.V.[R. Venkatesh],
Towards Efficient and Effective Self-supervised Learning of Visual Representations,
ECCV22(XXXI:523-538).
Springer DOI 2211
BibRef

Akiva, P.[Peri], Purri, M.[Matthew], Leotta, M.[Matthew],
Self-Supervised Material and Texture Representation Learning for Remote Sensing Tasks,
CVPR22(8193-8205)
IEEE DOI 2210
Representation learning, Satellites, Semantics, Transfer learning, Self-supervised learning, Surface texture, Task analysis, Photogrammetry and remote sensing BibRef

Du, Y.L.[Yi-Lun], Gan, C.[Chuang], Isola, P.[Phillip],
Curious Representation Learning for Embodied Intelligence,
ICCV21(10388-10397)
IEEE DOI 2203
Representation learning, Visualization, Navigation, Semantics, Reinforcement learning, Internet, Representation learning, BibRef

Zhou, H.Y.[Hong-Yu], Lu, C.X.[Chi-Xiang], Yang, S.[Sibei], Han, X.G.[Xiao-Guang], Yu, Y.Z.[Yi-Zhou],
Preservational Learning Improves Self-supervised Medical Image Models by Reconstructing Diverse Contexts,
ICCV21(3479-3489)
IEEE DOI 2203

WWW Link. Representation learning, Protocols, Codes, Computational modeling, Estimation, Task analysis, Medical, biological, and cell microscopy, BibRef

Huang, S.Y.[Si-Yuan], Xie, Y.C.[Yi-Chen], Zhu, S.C.[Song-Chun], Zhu, Y.X.[Yi-Xin],
Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds,
ICCV21(6515-6525)
IEEE DOI 2203
Point cloud compression, Representation learning, Training, Solid modeling, Visualization, Supervised learning, Stereo, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Hu, K.[Kai], Shao, J.[Jie], Liu, Y.[Yuan], Raj, B.[Bhiksha], Savvides, M.[Marios], Shen, Z.Q.[Zhi-Qiang],
Contrast and Order Representations for Video Self-Supervised Learning,
ICCV21(7919-7929)
IEEE DOI 2203
Representation learning, Computational modeling, Predictive models, Task analysis, Videos, Representation learning BibRef

Qian, R.[Rui], Ding, S.R.[Shuang-Rui], Liu, X.[Xian], Lin, D.[Dahua],
Static and Dynamic Concepts for Self-Supervised Video Representation Learning,
ECCV22(XXVI:145-164).
Springer DOI 2211
BibRef

Qian, R.[Rui], Li, Y.X.[Yu-Xi], Liu, H.B.[Hua-Bin], See, J.[John], Ding, S.R.[Shuang-Rui], Liu, X.[Xian], Li, D.[Dian], Lin, W.Y.[Wei-Yao],
Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization,
ICCV21(7970-7981)
IEEE DOI 2203
Representation learning, Codes, Computational modeling, Semantics, Reliability, Task analysis, Video analysis and understanding, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Huang, D.[Deng], Wu, W.H.[Wen-Hao], Hu, W.[Weiwen], Liu, X.[Xu], He, D.L.[Dong-Liang], Wu, Z.H.[Zhi-Hua], Wu, X.M.[Xiang-Miao], Tan, M.K.[Ming-Kui], Ding, E.[Errui],
ASCNet: Self-Supervised Video Representation Learning with Appearance-Speed Consistency,
ICCV21(8076-8085)
IEEE DOI 2203
Representation learning, Visualization, Image recognition, Codes, Noise measurement, Data mining, Video analysis and understanding, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Kim, D.H.[Dong-Hyun], Saito, K.[Kuniaki], Oh, T.H.[Tae-Hyun], Plummer, B.A.[Bryan A.], Sclaroff, S.[Stan], Saenko, K.[Kate],
CDS: Cross-Domain Self-supervised Pre-training,
ICCV21(9103-9112)
IEEE DOI 2203
Transfer learning, Task analysis, Standards, Transfer/Low-shot/Semi/Unsupervised Learning, Representation learning BibRef

Wang, G.[Guangrun], Wang, K.[Keze], Wang, G.[Guangcong], Torr, P.H.S.[Philip H.S.], Lin, L.[Liang],
Solving Inefficiency of Self-supervised Representation Learning,
ICCV21(9485-9495)
IEEE DOI 2203
Training, Representation learning, Computational modeling, Supervised learning, Benchmark testing, Task analysis, Representation learning BibRef

Patrick, M.[Mandela], Asano, Y.M.[Yuki M.], Kuznetsova, P.[Polina], Fong, R.[Ruth], Henriques, J.F.[João F.], Zweig, G.[Geoffrey], Vedaldi, A.[Andrea],
On Compositions of Transformations in Contrastive Self-Supervised Learning,
ICCV21(9557-9567)
IEEE DOI 2203
Codes, Benchmark testing, Encoding, Standards, Videos, Representation learning, Vision + other modalities BibRef

Hua, T.[Tianyu], Wang, W.X.[Wen-Xiao], Xue, Z.[Zihui], Ren, S.[Sucheng], Wang, Y.[Yue], Zhao, H.[Hang],
On Feature Decorrelation in Self-Supervised Learning,
ICCV21(9578-9588)
IEEE DOI 2203
Representation learning, Correlation, Robustness, Decorrelation, Covariance matrices, Representation learning, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Kotar, K.[Klemen], Ilharco, G.[Gabriel], Schmidt, L.[Ludwig], Ehsani, K.[Kiana], Mottaghi, R.[Roozbeh],
Contrasting Contrastive Self-Supervised Representation Learning Pipelines,
ICCV21(9929-9939)
IEEE DOI 2203
Representation learning, Training, Visualization, Pipelines, Benchmark testing, Data models, Representation learning, BibRef

Tian, Y.L.[Yong-Long], Hénaff, O.J.[Olivier J.], van den Oord, A.[Aäron],
Divide and Contrast: Self-supervised Learning from Uncurated Data,
ICCV21(10043-10054)
IEEE DOI 2203
Annotations, Benchmark testing, Data mining, Task analysis, Representation learning, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Zhao, Y.C.[Yu-Cheng], Wang, G.[Guangting], Luo, C.[Chong], Zeng, W.J.[Wen-Jun], Zha, Z.J.[Zheng-Jun],
Self-Supervised Visual Representations Learning by Contrastive Mask Prediction,
ICCV21(10140-10149)
IEEE DOI 2203
Training, Representation learning, Visualization, Head, Semantics, Performance gain, Representation learning, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Koohpayegani, S.A.[Soroush Abbasi], Tejankar, A.[Ajinkya], Pirsiavash, H.[Hamed],
Mean Shift for Self-Supervised Learning,
ICCV21(10306-10315)
IEEE DOI 2203
Codes, Clustering algorithms, Task analysis, Residual neural networks, Representation learning, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Gavrilyuk, K.[Kirill], Jain, M.[Mihir], Karmanov, I.[Ilia], Snoek, C.G.M.[Cees G. M.],
Motion-Augmented Self-Training for Video Recognition at Smaller Scale,
ICCV21(10409-10418)
IEEE DOI 2203
Training, Optical losses, Knowledge engineering, Computational modeling, Semisupervised learning, Action and behavior recognition BibRef

Pantazis, O.[Omiros], Brostow, G.J.[Gabriel J.], Jones, K.E.[Kate E.], Aodha, O.M.[Oisin Mac],
Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring,
ICCV21(10563-10572)
IEEE DOI 2203
Training, Visualization, Transfer learning, Benchmark testing, Cameras, Biodiversity, Representation learning, Medical, biological, Recognition and classification BibRef

Zhang, L.Z.[Ling-Zhi], Du, W.Y.[Wei-Yu], Zhou, S.H.[Sheng-Hao], Wang, J.C.[Jian-Cong], Shi, J.B.[Jian-Bo],
Inpaint2Learn: A Self-Supervised Framework for Affordance Learning,
WACV22(3778-3787)
IEEE DOI 2202
Training, Affordances, Pipelines, Predictive models, Benchmark testing, Adversarial machine learning, Analysis and Understanding Scene Understanding BibRef

Mazumder, P.[Pratik], Singh, P.[Pravendra], Namboodiri, V.P.[Vinay P.],
Fair Visual Recognition in Limited Data Regime using Self-Supervision and Self-Distillation,
WACV22(3889-3897)
IEEE DOI 2202
Training, Deep learning, Adaptation models, Visualization, Computational modeling, Training data, Privacy and Ethics in Vision BibRef

Zheltonozhskii, E.[Evgenii], Baskin, C.[Chaim], Mendelson, A.[Avi], Bronstein, A.M.[Alex M.], Litany, O.[Or],
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels,
WACV22(387-397)
IEEE DOI 2202
Training, Upper bound, Neural networks, Semisupervised learning, Feature extraction, Robustness, Transfer, Large-scale Vision Applications BibRef

Reed, C.J.[Colorado J.], Yue, X.Y.[Xiang-Yu], Nrusimha, A.[Ani], Ebrahimi, S.[Sayna], Vijaykumar, V.[Vivek], Mao, R.[Richard], Li, B.[Bo], Zhang, S.H.[Shang-Hang], Guillory, D.[Devin], Metzger, S.[Sean], Keutzer, K.[Kurt], Darrell, T.J.[Trevor J.],
Self-Supervised Pretraining Improves Self-Supervised Pretraining,
WACV22(1050-1060)
IEEE DOI 2202
Computational modeling, Data models, Robustness, Task analysis, X-ray imaging, Convergence, Transfer, Few-shot, Vision for Aerial/Drone/Underwater/Ground Vehicles BibRef

Zhang, Z.[Zehua], Crandall, D.[David],
Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning,
WACV22(975-985)
IEEE DOI 2202
Representation learning, Deep learning, Codes, Semantics, Supervised learning, Benchmark testing, Transfer, Analysis and Understanding BibRef

Huynh, T.[Tri], Kornblith, S.[Simon], Walter, M.R.[Matthew R.], Maire, M.[Michael], Khademi, M.[Maryam],
Boosting Contrastive Self-Supervised Learning with False Negative Cancellation,
WACV22(986-996)
IEEE DOI 2202
Representation learning, Visualization, Codes, Computational modeling, Semantics, Boosting, Transfer, Few-shot, Semi- and Un- supervised Learning Deep Learning BibRef

Yamaguchi, S.[Shin'ya], Kanai, S.[Sekitoshi], Shioda, T.[Tetsuya], Takeda, S.[Shoichiro],
Image Enhanced Rotation Prediction for Self-Supervised Learning,
ICIP21(489-493)
IEEE DOI 2201
Shape, Predictive models, Network architecture, Benchmark testing, Task analysis, Image enhancement, Self-supervised learning, CNN BibRef

Selvaraju, R.R.[Ramprasaath R.], Desai, K.[Karan], Johnson, J.[Justin], Naik, N.[Nikhil],
CASTing Your Model: Learning to Localize Improves Self-Supervised Representations,
CVPR21(11053-11062)
IEEE DOI 2111
Visualization, Correlation, Codes, Grounding, Crops, Robustness BibRef

Gudovskiy, D., Hodgkinson, A., Yamaguchi, T., Tsukizawa, S.,
Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision,
CVPR20(9038-9046)
IEEE DOI 2008
Task analysis, Training, Kernel, Labeling, Artificial intelligence, Data models, Training data BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Self-Supervised Learning for Object Detection and Segmentation .


Last update:May 22, 2023 at 22:32:27