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

Authors

785

  1. SF
    Steve Fotios

    University of Sheffield, United Kingdom

    4 publications · 178 citations

    4

    h-index

  2. LM
    Larry Matthies

    Jet Propulsion Laboratory, United States

    4 publications · 661 citations

    4

    h-index

  3. PC
    Pascual Campoy

    Universidad Politécnica de Madrid, Spain

    3 publications · 140 citations

    3

    h-index

  4. AR
    Arturo Rankin

    Jet Propulsion Laboratory, United States

    3 publications · 191 citations

    3

    h-index

  5. PP
    Pier Paolo Porta

    University of Parma, Italy

    3 publications · 96 citations

    3

    h-index

1–5 of 785

Venues

  1. Sensors

    9 publications · 420 citations

    7

    h-index

  2. 6

    h-index

  3. 6

    h-index

  4. Lighting Research & Technology

    4 publications · 178 citations

    4

    h-index

  5. Image and Vision Computing

    3 publications · 238 citations

    3

    h-index

1–5