Deep Learning-based Identification

Deep Learning-Based Identification is a methodological framework within computational plant science that employs deep neural networks to automatically detect and classify poisonous weeds from visual or spectral data, distinguishing itself from traditional image analysis techniques through its capacity for hierarchical feature learning and end-to-end pattern recognition.

2.3K

Publications

149.2K

Citations

9.6K

Authors

2.5K

Institutions

Publications per year

2017–2026

2.3K

Authors

9.6K

  1. VK
    Vinay Kukreja

    Chitkara University, India

    24 publications · 1.5K citations

    23

    h-index

  2. SM
    Shiva Mehta

    Chitkara University, India

    13 publications · 954 citations

    13

    h-index

  3. YH
    Yong He

    Zhejiang University, China

    12 publications · 522 citations

    12

    h-index

  4. AJ
    Alexis Joly

    UMR Botanique et Modélisation de l’Architecture des Plantes et des végétations, France

    11 publications · 824 citations

    11

    h-index

  5. HG
    Hervé Goëau

    UMR Botanique et Modélisation de l’Architecture des Plantes et des végétations, France

    10 publications · 760 citations

    10

    h-index

1–5 of 9.6K

Venues

  1. Computers and Electronics in Agriculture

    105 publications · 19.3K citations

    60

    h-index

  2. IEEE Access

    82 publications · 8.4K citations

    48

    h-index

  3. Frontiers in Plant Science

    67 publications · 8.3K citations

    33

    h-index

  4. Ecological Informatics

    46 publications · 2.9K citations

    31

    h-index

  5. Agriculture

    50 publications · 3.3K citations

    30

    h-index

1–5