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Deep neural networks (DNNs) have achieved great success in a wide variety of medical image analysis tasks.
“Loop: Local outlier probabilities,”
Hans-peter Kriegel, Erich Schubert, and Arthur Zimek, · 2009
Earlier work this paper cites.
“Automatic cerebral microbleeds detection from mr images via independent subspace analysis based hierarchical features,”
Qi Dou, Hao Chen, Lequan Yu, Lin Shi, Defeng Wang, Vincent CT Mok, and Pheng Ann Heng, · 2015
Earlier work this paper cites.
“Understanding deep learning requires rethinking generalization,”
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals, · 2017
Earlier work this paper cites.
“Training deep neural-networks using a noise adaptation layer,”
Jacob Goldberger and Ehud Ben-Reuven, · 2017
Earlier work this paper cites.
“Making deep neural networks robust to label noise: A loss correction approach,”
Giorgio Patrini, Alessandro Rozza, Aditya Krishna Menon, Richard Nock, and Lizhen Qu, · 2017
Earlier work this paper cites.
“Learning From Noisy Large-Scale Datasets With Minimal Supervision.,”
Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, and Serge J Belongie, · 2017
Cited alongside, same era.
“Automated pulmonary nodule detection via 3d convnets with online sample filtering and hybrid-loss residual learning,”
Qi Dou, Hao Chen, Yueming Jin, Huangjing Lin, Jing Qin, and Pheng-Ann Heng, · 2017
Cited alongside, same era.
“A Closer Look at Memorization in Deep Networks,”
Devansh Arpit, Stanisław Jastrzȩbski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, and Simon Lacoste-Julien, · 2017
Cited alongside, same era.
“MentorNet: Regularizing very deep neural networks on corrupted labels,”
Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, and Li Fei-Fei, · 2018
Cited alongside, same era.
“Joint optimization framework for learning with noisy labels,”
Daiki Tanaka, Daiki Ikami, Toshihiko Yamasaki, and Kiyoharu Aizawa, · 2018
Later among the works it cites.
“Learning to reweight examples for robust deep learning,”
Mengye Ren, Wenyuan Zeng, Bin Yang, and Raquel Urtasun, · 2018
Later among the works it cites.
“Training a neural network based on unreliable human annotation of medical images,”
Yair Dgani, Hayit Greenspan, and Jacob Goldberger, · 2018
Later among the works it cites.
“Skin lesion analysis toward melanoma detection: A challenge at the 2017 international symposium on biomedical imaging (isbi), hosted by the international skin imaging collaboration (isic),”
Noel C.F. Codella et al., · 2018
Later among the works it cites.
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