Multi-scale Feature Detection
Multi-Scale Feature Detection is a computational method in computer vision that identifies image features across multiple spatial scales to enhance robustness to variations in size, resolution, and distance by systematically analyzing structures at differing levels of detail.
698
Publications
46.6K
Citations
2.4K
Authors
621
Institutions
Publications per year
2017–2026
577
Parents
698
EfficientDet: Scalable and Efficient Object Detection
Mingxing Tan, Ruoming Pang, Quoc V. Le · 2020 · 8.4K citations
Andrea Vedaldi, Brian Fulkerson · 2010 · 2.7K citations
The Fastest Pedestrian Detector in the West
Piotr Dollár, Serge Belongie, Pietro Perona · 2010 · 569 citations · Full text
1–5 of 698
2.4K
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Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates
3 publications · 129 citations
3
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1–5 of 2.4K
621

Chinese Academy of Sciences
Beijing, China
20 h-index
88 publications
11.3K citations
University of Chinese Academy of Sciences
Beijing, China
16 h-index
49 publications
5.4K citations

Xidian University
Xi'an, China
13 h-index
61 publications
2.5K citations

Beihang University
Beijing, China
13 h-index
31 publications
1.4K citations
Wuhan University
Wuhan, China
12 h-index
37 publications
2.9K citations
Nanyang Technological University
Singapore, Singapore
10 h-index
25 publications
1.5K citations

South China University of Technology
Guangzhou, China
10 h-index
33 publications
1.1K citations

Southeast University
Nanjing, China
10 h-index
24 publications
749 citations
1–8 of 621
28 publications · 2K citations
24
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36 publications · 1.7K citations
24
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22 publications · 1.1K citations
19
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13 publications · 700 citations
15
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12 publications · 779 citations
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