Small Obstacle Detection
Small Obstacle Detection is a specialized method within obstacle detection that focuses on identifying and localizing low-sized, often ground-level objects in sensor data, distinguished by their reduced physical dimensions and heightened challenge to perception systems due to limited visual or LiDAR signatures.
221
Publications
11.1K
Citations
785
Authors
283
Institutions
Publications per year
2017–2026
100
Parents
221
RSOD: Real-time small object detection algorithm in UAV-based traffic monitoring
Wei Sun, Liang Dai, Xiaorui Zhang et al. · Applied Intelligence · 2021 · 270 citations
1–5 of 221
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283
Carnegie Mellon University
Pittsburgh, United States
6 h-index
15 publications
1.1K citations
University of Sheffield
Sheffield, United Kingdom
5 h-index
14 publications
499 citations

Universidad Politécnica de Madrid
Madrid, Spain
4 h-index
9 publications
428 citations
Jet Propulsion Laboratory
Pasadena, United States
4 h-index
12 publications
2K citations

University of Parma
Parma, Italy
3 h-index
15 publications
642 citations

Parthenope University of Naples
Naples, Italy
3 h-index
6 publications
97 citations

Nanjing University of Aeronautics and Astronautics
Nanjing, China
3 h-index
7 publications
573 citations
Brigham Young University
Provo, United States
3 h-index
12 publications
764 citations
1–8 of 283
9 publications · 420 citations
7
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6 publications · 154 citations
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6 publications · 481 citations
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4 publications · 178 citations
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3 publications · 238 citations
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