Pooling Operations is a computational mechanism in neural network architectures that reduces the spatial dimensions of feature maps by summarizing regions through aggregation functions such as maximum or average values, thereby enabling hierarchical feature abstraction while maintaining translation invariance.
211
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28.3K
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790
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316
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Publications per year
2017–2026
150
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Publications
211
A Theoretical Analysis of Feature Pooling in Visual Recognition
Y-Lan Boureau, Jean Ponce, Yann LeCun · 2010 · 1.2K citations
A Simple Convolutional Generative Network for Next Item Recommendation
Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis et al. · 2019 · 625 citations · Full text
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316
New York University
New York, United States
8 h-index
19 publications
5.6K citations
Chinese Academy of Sciences
Beijing, China
7 h-index
13 publications
586 citations
Courant Institute of Mathematical Sciences
New York, United States
5 h-index
14 publications
4.5K citations
Institute of Automation
Beijing, China
5 h-index
14 publications
640 citations
Nanjing University of Information Science and Technology
Nanjing, China
4 h-index
9 publications
646 citations
University of California San Diego
San Diego, United States
4 h-index
9 publications
1.4K citations
Peking University
Beijing, China
4 h-index
16 publications
627 citations
Monash University
Melbourne, Australia
3 h-index
10 publications
1.5K citations
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Repository · 22 publications · 2.8K citations
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14 publications · 1.1K citations
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- Multimedia Tools and Applications
6 publications · 204 citations
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- Neurocomputing
6 publications · 161 citations
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- IEEE Transactions on Geoscience and Remote Sensing
4 publications · 290 citations
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