Model-based Plant Identification

Model-Based Plant Identification is a systematic approach within computational plant science that employs formal models—such as machine learning algorithms, morphological templates, or spectral signature profiles—to enable the automated recognition and classification of poisonous weeds by distinguishing diagnostic features from background vegetation.

74

Publications

3.4K

Citations

255

Authors

127

Institutions

Publications per year

2017–2026

24

Authors

255

  1. XH
    Xinyuan Huang

    Beijing Forestry University, China

    2 publications · 63 citations

    2

    h-index

  2. HZ
    Heyan Zhu

    Harbin Institute of Technology, China

    2 publications · 63 citations

    2

    h-index

  3. RY
    Rick Younce

    University of Notre Dame, United States

    2 publications · 83 citations

    2

    h-index

  4. CR
    C.E. Rohrs

    Massachusetts Institute of Technology, United States

    2 publications · 83 citations

    2

    h-index

  5. JO
    João Onofre Pereira Pinto

    Universidade Federal de Mato Grosso do Sul, Brazil

    2 publications · 79 citations

    2

    h-index

1–5 of 255

Venues

  1. Multimedia Tools and Applications

    2 publications · 63 citations

    2

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 52 citations

    2

    h-index

  3. Automatica

    2 publications · 189 citations

    2

    h-index

  4. 2

    h-index

  5. Ecological Informatics

    2 publications · 90 citations

    2

    h-index

1–5