Multi-scale Feature Extraction
Multi-Scale Feature Extraction is a feature engineering technique that captures structural patterns at multiple spatial or temporal resolutions by differentially analyzing image data through a hierarchy of scales, thereby enabling the representation of both fine-grained and coarse-grained visual characteristics within a unified framework.
947
Publications
52K
Citations
3.9K
Authors
873
Institutions
Publications per year
2017–2026
815
Parents
947
Pyramid Feature Attention Network for Saliency Detection
Ting Zhao, Xiangqian Wu · 2019 · 775 citations
DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
Hanchao Li, Pengfei Xiong, Haoqiang Fan et al. · 2019 · 698 citations
1–5 of 947
3.9K
Nanjing University of Information Science and Technology, China
9 publications · 504 citations
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873

Chinese Academy of Sciences
Beijing, China
25 h-index
116 publications
6.1K citations
Wuhan University
Wuhan, China
23 h-index
96 publications
9.6K citations

Xidian University
Xi'an, China
22 h-index
119 publications
5.8K citations

Nanjing University of Information Science and Technology
Nanjing, China
19 h-index
63 publications
2.9K citations

Peking University
Beijing, China
19 h-index
79 publications
3.4K citations
University of Chinese Academy of Sciences
Beijing, China
18 h-index
63 publications
3K citations

Huazhong University of Science and Technology
Wuhan, China
16 h-index
42 publications
2.3K citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
14 h-index
40 publications
3.2K citations
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59 publications · 2.3K citations
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50 publications · 2.4K citations
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Repository · 47 publications · 1.6K citations
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33 publications · 1.3K citations
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18 publications · 1.6K citations
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