Multi-sensor Perception
Multi-Sensor Perception is a systematic framework in sense-and-avoid systems that integrates data from multiple heterogeneous sensing modalities to achieve enhanced environmental awareness and object detection accuracy beyond the capabilities of individual sensors.
123
Publications
6.9K
Citations
487
Authors
211
Institutions
Publications per year
2017–2026
69
Parents
123
Cooper: Cooperative Perception for Connected Autonomous Vehicles Based on 3D Point Clouds
Qi Chen, Sihai Tang, Qing Yang et al. · 2019 · 381 citations
Ze Liu, Yingfeng Cai, Hai Wang et al. · IEEE Transactions on Intelligent Transportation Systems · 2021 · 311 citations
1–5 of 123
487
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1–5 of 487
211
University of California, Los Angeles
Los Angeles, United States
5 h-index
20 publications
2.2K citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
10 publications
530 citations
Dalian University of Technology
Dalian, China
3 h-index
7 publications
221 citations
Technical University of Munich
Munich, Germany
3 h-index
9 publications
770 citations

University of Edinburgh
Edinburgh, United Kingdom
3 h-index
5 publications
230 citations

The University of Sydney
Sydney, Australia
2 h-index
4 publications
234 citations
National University of Singapore
Singapore, Singapore
2 h-index
5 publications
91 citations

University of North Texas
Denton, United States
2 h-index
8 publications
1.6K citations
1–8 of 211
Repository · 7 publications · 132 citations
7
h-index
7 publications · 161 citations
6
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4 publications · 740 citations
3
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3 publications · 66 citations
3
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3 publications · 651 citations
3
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1–5