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

Authors

194

  1. RU
    Raquel Urtasun

    University of Toronto, Canada

    3 publications · 1.2K citations

    3

    h-index

  2. JF
    Julian F. P. Kooij

    Delft University of Technology, Netherlands

    2 publications · 288 citations

    2

    h-index

  3. ML
    Ming Liang

    University of Toronto, Canada

    2 publications · 448 citations

    2

    h-index

  4. JP
    Jonne Poikonen

    University of Turku, Finland

    2 publications · 54 citations

    2

    h-index

  5. ML
    Markus Laurinen

    University of Turku, Finland

    2 publications · 54 citations

    2

    h-index

1–5 of 194

Venues

  1. Sensors

    3 publications · 67 citations

    3

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 655 citations

    3

    h-index

  3. IEEE Robotics and Automation Letters

    2 publications · 290 citations

    2

    h-index

  4. 2

    h-index

  5. Remote Sensing

    2 publications · 43 citations

    2

    h-index

1–5