Feature Summation
Feature Summation is a feature aggregation method that computes the combined representation of input features by applying element-wise addition, distinguishing itself from other aggregation techniques through its additive composition without normalization or weighting.
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2017–2026
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SEMBLANCE AND OTHER COHERENCY MEASURES FOR MULTICHANNEL DATA
Norman S. Neidell, M. Turhan Taner · Geophysics · 1971 · 846 citations
Joint Fine-Tuning in Deep Neural Networks for Facial Expression Recognition
Heechul Jung, Sihaeng Lee, Junho Yim et al. · 2015 · 771 citations
Expectation-Maximization Attention Networks for Semantic Segmentation
Xia Li, Zhisheng Zhong, Jianlong Wu et al. · 2019 · 652 citations
Gated Convolutional Neural Network for Semantic Segmentation in High-Resolution Images
Hongzhen Wang, Ying Wang, Qian Zhang et al. · Remote Sensing · 2017 · 207 citations · Full text
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University of Wisconsin–Madison
Madison, United States
3 h-index
9 publications
150 citations
University of Chinese Academy of Sciences
Beijing, China
2 h-index
3 publications
237 citations

Drexel University
Philadelphia, United States
2 h-index
4 publications
97 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
5 publications
907 citations
University College London
London, United Kingdom
2 h-index
5 publications
141 citations
National Chung Cheng University
Minxiong, Taiwan
2 h-index
2 publications
34 citations
Georgia State University
Atlanta, United States
2 h-index
6 publications
180 citations

Uppsala University
Uppsala, Sweden
2 h-index
2 publications
56 citations
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4 publications · 147 citations
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GRSL · 2 publications · 103 citations
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2 publications · 36 citations
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2 publications · 279 citations
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Repository · 1 publications · 17 citations
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