Visual Victim Detection

Visual Victim Detection is a computational method within the domain of disaster response and surveillance systems that distinguishes itself by automatically identifying human victims in distress through the analysis of visual data collected from aerial, ground-based, or robotic imaging sources.

50

Publications

2.3K

Citations

193

Authors

64

Institutions

Publications per year

2017–2026

35

Authors

193

  1. IA
    Indra Adji Sulistijono

    Politeknik Elektronika Negeri Surabaya

    2 publications · 31 citations

    2

    h-index

  2. MI
    Muhammad Ilham Perdana

    Robotic Research (United States), United States

    2 publications · 31 citations

    2

    h-index

  3. BM
    Bartłomiej Miziński

    University of Wrocław, Poland

    2 publications · 46 citations

    2

    h-index

  4. MJ
    Mirosława Jurecka

    University of Wrocław, Poland

    2 publications · 46 citations

    2

    h-index

  5. MG
    Michał Grega

    AGH University of Krakow, Poland

    2 publications · 211 citations

    2

    h-index

1–5 of 193

Venues

  1. Remote Sensing

    4 publications · 341 citations

    4

    h-index

  2. Sensors

    3 publications · 308 citations

    3

    h-index

  3. International Journal of Legal Medicine

    2 publications · 92 citations

    2

    h-index

  4. IEEE Access

    2 publications · 182 citations

    2

    h-index

  5. Modeling Earth Systems and Environment

    MESE · 1 publications · 30 citations

    1

    h-index

1–5