Attention Mechanisms
Attention Mechanism is a computational model in deep learning that selectively enhances or suppresses elements of input representations by dynamically assigning varying weights to different parts of the data, based on their relevance to the current processing task.
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DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · 2023 · 76.3K citations · Full text
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
Qilong Wang, Banggu Wu, Pengfei Zhu et al. · 2020 · 8.1K citations
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Kelvin Xu, Jimmy Ba, Ryan Kiros et al. · arXiv (Cornell University) · 2015 · 7.5K citations · Full text
Ashish Vaswani, Noam Shazeer, Niki Parmar et al. · 2025 · 6.6K citations · Full text
Coordinate Attention for Efficient Mobile Network Design
Qibin Hou, Daquan Zhou, Jiashi Feng · 2021 · 5.7K citations
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Chinese Academy of Sciences
Beijing, China
43 h-index
282 publications
19.4K citations
University of Chinese Academy of Sciences
Beijing, China
38 h-index
153 publications
12.1K citations
Tsinghua University
Beijing, China
35 h-index
159 publications
41.6K citations

Peking University
Beijing, China
28 h-index
95 publications
12.9K citations

Zhejiang University
Hangzhou, China
28 h-index
117 publications
13.1K citations
University of Science and Technology of China
Hefei, China
28 h-index
115 publications
11.2K citations
Google (United States)
Mountain View, United States
28 h-index
125 publications
23.8K citations

Northwestern Polytechnical University
Xi'an, China
28 h-index
104 publications
5K citations
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Repository · 349 publications · 36.1K citations
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Conference · 56 publications · 4.9K citations
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