Sparse Feature Aggregation
Sparse Feature Aggregation is a computational method that selectively combines a small subset of salient features from high-dimensional, sparsely activated representations to produce compact and informative aggregate feature vectors.
26
Publications
1.7K
Citations
99
Authors
42
Institutions
Publications per year
2017–2026
21
Parents
26
Learning A Sparse Transformer Network for Effective Image Deraining
Xiang Chen, Hao Li, Mingqiang Li et al. · 2023 · 439 citations
Histograms of Sparse Codes for Object Detection
Xiaofeng Ren, Deva Ramanan · 2013 · 242 citations
Sparse Graph Attention Networks
Shihao Ji · IEEE Transactions on Knowledge and Data Engineering · 2021 · 191 citations
1–5 of 26
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42
Nanjing University of Science and Technology
Nanjing, China
4 h-index
12 publications
1.7K citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
6 publications
73 citations
University of Connecticut
Storrs, United States
1 h-index
1 publications
17 citations
University of California, Irvine
Irvine, United States
1 h-index
1 publications
242 citations
Georgia State University
Atlanta, United States
1 h-index
2 publications
382 citations
China Electronics Technology Group Corporation
Beijing, China
1 h-index
1 publications
439 citations
University of Geneva
Geneva, Switzerland
1 h-index
2 publications
96 citations

Chinese Academy of Sciences
Beijing, China
1 h-index
4 publications
100 citations
1–8 of 42
Repository · 4 publications · 96 citations
4
h-index
1 publications · 16 citations
1
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TKDE · 1 publications · 191 citations
1
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1 publications · 24 citations
1
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1 publications · 16 citations
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1–5