Global Pooling is a type of pooling operation in deep learning that reduces an entire feature map to a single scalar value per channel by applying a global aggregation function such as maximum or average, thereby preserving only the most salient spatial information across the full extent of the input.
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Global Pooling Operation
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310
Learning Deep Features for Discriminative Localization
Bolei Zhou, Aditya Khosla, Àgata Lapedriza et al. · 2016 · 10.8K citations · Full text
Coordinate Attention for Efficient Mobile Network Design
Qibin Hou, Daquan Zhou, Jiashi Feng · 2021 · 5.7K citations
Min Lin, Qiang Chen, Shuicheng Yan · arXiv (Cornell University) · 2013 · 2K citations · Full text
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Chinese Academy of Sciences
Beijing, China
9 h-index
19 publications
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University of Chinese Academy of Sciences
Beijing, China
8 h-index
23 publications
868 citations
Huazhong University of Science and Technology
Wuhan, China
8 h-index
30 publications
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Dalian University of Technology
Dalian, China
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Tsinghua University
Beijing, China
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14 publications
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Tianjin University
Tianjin, China
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Harbin Institute of Technology
Harbin, China
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Peking University
Beijing, China
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