Robust Weed Classification

Robust Weed Classification is a methodological framework within vegetative weed identification that systematically enhances classification accuracy and consistency across diverse environmental conditions, plant growth stages, and imaging variations by integrating adaptive feature extraction, noise resilience, and generalizable decision rules.

9

Publications

852

Citations

48

Authors

15

Institutions

Publications per year

2017–2026

7

Authors

48

  1. JJ
    Jamie Johns

    James Cook University, Australia

    1 publications · 492 citations

    1

    h-index

  2. BM
    Bethany Melville

    University of Tasmania, Australia

    1 publications · 58 citations

    1

    h-index

  3. JW
    Jan Weyler

    University of Bonn, Germany

    1 publications · 31 citations

    1

    h-index

  4. MD
    Mads Dyrmann

    Aarhus University, Denmark

    1 publications · 25 citations

    1

    h-index

  5. AO
    Alex Olsen

    James Cook University, Australia

    1 publications · 492 citations

    1

    h-index

1–5 of 48

Venues

  1. IEEE Robotics and Automation Letters

    1 publications · 31 citations

    1

    h-index

  2. Precision Agriculture

    1 publications · 19 citations

    1

    h-index

  3. 1

    h-index

  4. PLoS ONE

    1 publications · 63 citations

    1

    h-index

  5. Scientific Reports

    1 publications · 492 citations

    1

    h-index

1–5