Cross-entropy Loss
Cross-Entropy Loss is a loss function that measures the dissimilarity between predicted probability distributions and true class labels in classification tasks by quantifying the divergence using the negative log-likelihood of the correct class under the softmax or sigmoid output.
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2017–2026
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Focal Loss for Dense Object Detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick et al. · 2017 · 25.7K citations
Focal Loss for Dense Object Detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2018 · 9.6K citations
Least Squares Generative Adversarial Networks
Xudong Mao, Qing Li, Haoran Xie et al. · 2017 · 5.2K citations
A Tutorial on the Cross-Entropy Method
Pieter-Tjerk de Boer, Dirk P. Kroese, Shie Mannor et al. · Annals of Operations Research · 2005 · 3K citations · Full text
BASNet: Boundary-Aware Salient Object Detection
Xuebin Qin, Zichen Zhang, Chenyang Huang et al. · 2019 · 1.6K citations
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Chinese Academy of Sciences
Beijing, China
27 h-index
144 publications
12.2K citations

Shanghai Jiao Tong University
Shanghai, China
22 h-index
78 publications
9.7K citations
Tsinghua University
Beijing, China
22 h-index
88 publications
5K citations

Zhejiang University
Hangzhou, China
21 h-index
72 publications
6.6K citations

Peking University
Beijing, China
18 h-index
52 publications
7.6K citations
University of Chinese Academy of Sciences
Beijing, China
18 h-index
88 publications
5.7K citations
Wuhan University
Wuhan, China
17 h-index
66 publications
3.1K citations
Google (United States)
Mountain View, United States
16 h-index
58 publications
5.5K citations
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Repository · 209 publications · 15.2K citations
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Conference · 30 publications · 2.8K citations
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