Image-based Larval Recognition

Image-Based Larval Recognition is a computational method that distinguishes individual larval species or developmental stages through the analysis of visual features extracted from digital images, differing from other larval identification techniques by relying exclusively on morphological patterns captured in imaging data rather than molecular, behavioral, or manual taxonomic examination.

13

Publications

336

Citations

76

Authors

31

Institutions

Publications per year

2017–2026

7

Authors

76

  1. MT
    Mai Togawa

    Japan Fisheries Research and Education Agency, Japan

    1 publications · 22 citations

    1

    h-index

  2. JM
    José Marcato

    Universidade Federal de Mato Grosso do Sul, Brazil

    1 publications · 24 citations

    1

    h-index

  3. CB
    Carolina Berini

    Universidad de Buenos Aires, Argentina

    1 publications · 40 citations

    1

    h-index

  4. MR
    Mohd Ruddin Ab Ghani

    Technical University of Malaysia Malacca, Malaysia

    1 publications · 23 citations

    1

    h-index

  5. KM
    Kitty McKnight

    CSIRO Land and Water, Australia

    1 publications · 10 citations

    1

    h-index

1–5 of 76

Venues

  1. Aquacultural Engineering

    2 publications · 46 citations

    2

    h-index

  2. Journal of Food Protection

    2 publications · 41 citations

    2

    h-index

  3. Journal of Sea Research

    JSR · 1 publications · 44 citations

    1

    h-index

  4. Agriculture and Natural Resources

    1 publications · 32 citations

    1

    h-index

  5. Ecotoxicology and Environmental Safety

    EES · 1 publications · 10 citations

    1

    h-index

1–5