Machine Vision For Pruning

Machine Vision for Pruning is a machine vision system that enables automated identification and localization of plant structures requiring pruning through image-based analysis, distinguishing it from general agricultural imaging techniques by its specific integration with pruning decision-making and robotic actuation in precision horticulture.

15

Publications

871

Citations

71

Authors

28

Institutions

Publications per year

2017–2026

7

Authors

71

  1. NE
    Noha Elfiky

    Purdue University West Lafayette, United States

    3 publications · 110 citations

    3

    h-index

  2. SA
    Shayan A. Akbar

    Purdue University West Lafayette, United States

    3 publications · 110 citations

    3

    h-index

  3. AC
    Avinash C. Kak

    Purdue University West Lafayette, United States

    2 publications · 60 citations

    2

    h-index

  4. MP
    María P. Diago

    Universidad de La Rioja, Spain

    1 publications · 18 citations

    1

    h-index

  5. KB
    Karly Burch

    University of Otago, New Zealand

    1 publications · 31 citations

    1

    h-index

1–5 of 71

Venues

  1. Biosystems Engineering

    2 publications · 60 citations

    2

    h-index

  2. Computers and Electronics in Agriculture

    2 publications · 509 citations

    2

    h-index

  3. 1

    h-index

  4. Neural Processing Letters

    1 publications · 17 citations

    1

    h-index

  5. Postharvest Biology and Technology

    1 publications · 19 citations

    1

    h-index

1–5