Multi-sensor Object Detection
Multi-Sensor Object Detection is a method in object detection fusion that integrates data from multiple heterogeneous sensors to localize and classify objects, distinguished by its reliance on cross-modal inputs to enhance detection accuracy and robustness in complex environments.
52
Publications
3.7K
Citations
194
Authors
88
Institutions
Publications per year
2017–2026
42
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52
Multi-Task Multi-Sensor Fusion for 3D Object Detection
Ming Liang, Bin Yang, Yun Chen et al. · 2019 · 761 citations
Deep Continuous Fusion for Multi-Sensor 3D Object Detection
Ming Liang, Bin Yang, Shenlong Wang et al. · arXiv (Cornell University) · 2020 · 431 citations · Full text
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88

Delft University of Technology
Delft, The Netherlands
2 h-index
6 publications
1.3K citations

University of Toronto
Toronto, Canada
2 h-index
5 publications
1.6K citations

University of Turku
Turku, Finland
2 h-index
11 publications
305 citations
Advanced Technologies Group (United States)
Stuart, United States
2 h-index
9 publications
5.5K citations
Michigan Technological University
Houghton, United States
1 h-index
3 publications
75 citations
University of Tennessee at Knoxville
Knoxville, United States
1 h-index
2 publications
738 citations

Sinclair Community College
Dayton, United States
1 h-index
1 publications
21 citations

Zhejiang University
Hangzhou, China
1 h-index
5 publications
1.2K citations
1–8 of 88
3 publications · 67 citations
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Repository · 3 publications · 655 citations
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2 publications · 290 citations
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2 publications · 106 citations
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2 publications · 43 citations
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