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Elsevier DOI
0501
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Self-Supervised Learning for Object Recognition based on Kernel
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IEEE DOI
0106
BibRef
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Yang, X.L.[Xu-Lei],
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SeSe-Net: Self-Supervised deep learning for segmentation,
PRL(128), 2019, pp. 23-29.
Elsevier DOI
1912
Self-Supervised learning, Deep learning, Segmentation, U-Net
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On the robustness of self-supervised representations for multi-view
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2209
Deep learning, Self-supervised learning, Representation learning
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Zhang, P.[Peng],
Huang, W.[Wei],
Zha, Y.F.[Yu-Fei],
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Zhang, Y.N.[Yan-Ning],
Object detection based on cortex hierarchical activation in border
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PR(137), 2023, pp. 109278.
Elsevier DOI
2302
Border sensitive mechanism, Cortex hierarchical activation,
Object detection, Classification-GIoU joint representation
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Hénaff, O.J.[Olivier J.],
Koppula, S.[Skanda],
Shelhamer, E.[Evan],
Zoran, D.[Daniel],
Jaegle, A.[Andrew],
Zisserman, A.[Andrew],
Carreira, J.[João],
Arandjelovic, R.[Relja],
Object Discovery and Representation Networks,
ECCV22(XXVII:123-143).
Springer DOI
2211
BibRef
Cui, Z.T.[Zi-Teng],
Zhu, Y.Y.[Ying-Ying],
Gu, L.[Lin],
Qi, G.J.[Guo-Jun],
Li, X.X.[Xiao-Xiao],
Zhang, R.[Renrui],
Zhang, Z.H.[Zeng-Hui],
Harada, T.[Tatsuya],
Exploring Resolution and Degradation Clues as Self-supervised Signal
for Low Quality Object Detection,
ECCV22(IX:473-491).
Springer DOI
2211
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Hénaff, O.J.[Olivier J.],
Koppula, S.[Skanda],
Alayrac, J.B.[Jean-Baptiste],
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Carreira, J.[João],
Efficient Visual Pretraining with Contrastive Detection,
ICCV21(10066-10076)
IEEE DOI
2203
Visualization, Transfer learning, Performance gain,
Feature extraction, Data models, Computational efficiency,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Yang, C.[Ceyuan],
Wu, Z.R.[Zhi-Rong],
Zhou, B.[Bolei],
Lin, S.[Stephen],
Instance Localization for Self-supervised Detection Pretraining,
CVPR21(3986-3995)
IEEE DOI
2111
Location awareness, Transfer learning, Semantics,
Object detection, Pattern recognition
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Ericsson, L.[Linus],
Gouk, H.[Henry],
Hospedales, T.M.[Timothy M.],
How Well Do Self-Supervised Models Transfer?,
CVPR21(5410-5419)
IEEE DOI
2111
Visualization, Image recognition,
Image color analysis, Computational modeling, Object detection,
Predictive models
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Ayush, K.[Kumar],
Uzkent, B.[Burak],
Meng, C.L.[Chen-Lin],
Tanmay, K.[Kumar],
Burke, M.[Marshall],
Lobell, D.[David],
Ermon, S.[Stefano],
Geography-Aware Self-Supervised Learning,
ICCV21(10161-10170)
IEEE DOI
2203
Training, Image segmentation, Supervised learning, Semantics,
Object detection, Task analysis, Representation learning,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Xiong, Y.[Yuwen],
Ren, M.[Mengye],
Zeng, W.Y.[Wen-Yuan],
Waabi, R.U.[Raquel Urtasun],
Self-Supervised Representation Learning from Flow Equivariance,
ICCV21(10171-10180)
IEEE DOI
2203
Representation learning, Image segmentation, Semantics, Crops,
Object detection, Streaming media, Representation learning,
Vision for robotics and autonomous vehicles
BibRef
Zhang, Z.[Zaiwei],
Girdhar, R.[Rohit],
Joulin, A.[Armand],
Misra, I.[Ishan],
Self-Supervised Pretraining of 3D Features on any Point-Cloud,
ICCV21(10232-10243)
IEEE DOI
2203
Training, Solid modeling, Image recognition, Object detection,
Representation learning,
3D from multiview and other sensors
BibRef
Chen, T.L.[Tian-Long],
Frankle, J.[Jonathan],
Chang, S.Y.[Shi-Yu],
Liu, S.J.[Si-Jia],
Zhang, Y.[Yang],
Carbin, M.[Michael],
Wang, Z.Y.[Zhang-Yang],
The Lottery Tickets Hypothesis for Supervised and Self-supervised
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CVPR21(16301-16311)
IEEE DOI
2111
Degradation, Image segmentation, Sensitivity,
Computational modeling, Perturbation methods, Pattern recognition
BibRef
Li, Y.D.[Yan-Dong],
Huang, D.[Di],
Qin, D.F.[Dan-Feng],
Wang, L.Q.[Li-Qiang],
Gong, B.Q.[Bo-Qing],
Improving Object Detection with Selective Self-supervised Self-training,
ECCV20(XXIX: 589-607).
Springer DOI
2010
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Lee, W.[Wonhee],
Na, J.[Joonil],
Kim, G.[Gunhee],
Multi-Task Self-Supervised Object Detection via Recycling of Bounding
Box Annotations,
CVPR19(4979-4988).
IEEE DOI
2002
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Multiple Instance Learning .