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Recently, self-supervised instance discrimination methods have achieved significant success in learning visual representations from unlabeled photographic images.
Joint generative and contrastive learning for unsupervised person re-identification
Hao Chen, Yaohui Wang, Benoit Lagadec, Antitza Dantcheva, and Francois Bremond · 2013
Earlier work this paper cites.
Two public chest x-ray datasets for computer-aided screening of pulmonary diseases
Stefan Jaeger, Sema Candemir, Sameer Antani, Yì-Xiáng J Wáng, Pu-Xuan Lu, and George Thoma · 2014
Earlier work this paper cites.
Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
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Improved regularization of convolutional neural networks with cutout, 2017
Terrance DeVries and Graham W. Taylor · 2017
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Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M Summers · 2017
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URL https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/
Siim-acr pneumothorax segmentation, 2019 · 2019
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Self-supervised learning for medical image analysis using image context restoration
Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, and Daniel Rueckert · 2019
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Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison
Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, et al · 2019
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Similarity of neural network representations revisited
Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey Hinton · 2019
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wav2vec: Unsupervised pre-training for speech recognition, 2019
Steffen Schneider, Alexei Baevski, Ronan Collobert, and Michael Auli · 2019
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Representation learning with contrastive predictive coding, 2019
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2019
Cited alongside, same era.
A critical analysis of self-supervision, or what we can learn from a single image, 2020
Yuki M. Asano, Christian Rupprecht, and Andrea Vedaldi · 2020
Cited alongside, same era.
Contrastive learning of global and local features for medical image segmentation with limited annotations
Krishna Chaitanya, Ertunc Erdil, Neerav Karani, and Ender Konukoglu · 2020
Cited alongside, same era.
Bootstrap your own latent - a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, koray kavukcuoglu, Remi Munos, and Michal Valko · 2020
Cited alongside, same era.
Learning semantics-enriched representation via self-discovery, self-classification, and self-restoration
Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael B. Gotway, and Jianming Liang · 2020
Cited alongside, same era.
Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 2021
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Revisiting contrastive methods for unsupervised learning of visual representations, 2021
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, and Luc Van Gool · 2021
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Transferable visual words: Exploiting the semantics of anatomical patterns for self-supervised learning
Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael B. Gotway, and Jianming Liang · 2021
Later among the works it cites.
A systematic benchmarking analysis of transfer learning for medical image analysis
Mohammad Reza Hosseinzadeh Taher, Fatemeh Haghighi, Ruibin Feng, Michael B. Gotway, and Jianming Liang · 2021
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A broad study on the transferability of visual representations with contrastive learning
Ashraful Islam, Chun-Fu (Richard) Chen, Rameswar Panda, Leonid Karlinsky, Richard Radke, and Rogerio Feris · 2021
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Cited alongside, same era.
What is being transferred in transfer learning?
Behnam Neyshabur, Hanie Sedghi, and Chiyuan Zhang · 2020
Cited alongside, same era.
Understanding contrastive representation learning through alignment and uniformity on the hypersphere
Tongzhou Wang and Phillip Isola · 2020
Cited alongside, same era.
Comparing to learn: Surpassing imagenet pretraining on radiographs by comparing image representations
Hong-Yu Zhou, Shuang Yu, Cheng Bian, Yifan Hu, Kai Ma, and Yefeng Zheng · 2020
Cited alongside, same era.
Big self-supervised models advance medical image classification
Shekoofeh Azizi, Basil Mustafa, Fiona Ryan, Zachary Beaver, Jan Freyberg, Jonathan Deaton, Aaron Loh, Alan Karthikesalingam, Simon Kornblith, Ting Chen, Vivek Natarajan, and Mohammad Norouzi · 2021
Cited alongside, same era.
Large-margin contrastive learning with distance polarization regularizer
Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, and Masashi Sugiyama
Cited in the paper.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton
Cited in the paper.
Intermediate layers matter in momentum contrastive self supervised learning, 2021
Aakash Kaku, Sahana Upadhya, and Narges Razavian · 2021
Later among the works it cites.
Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
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What makes instance discrimination good for transfer learning?
Nanxuan Zhao, Zhirong Wu, Rynson W. H. Lau, and Stephen Lin · 2021
Later among the works it cites.
Preservational learning improves self-supervised medical image models by reconstructing diverse contexts
Hong-Yu Zhou, Chixiang Lu, Sibei Yang, Xiaoguang Han, and Yizhou Yu · 2021
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Dira: Discriminative, restorative, and adversarial learning for self-supervised medical image analysis
Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Michael B. Gotway, and Jianming Liang · 2022
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