Machine Vision Guidance

Machine Vision Guidance is a systematic method within automated spraying systems that employs image processing and pattern recognition algorithms to dynamically direct spray nozzles by real-time identification and localization of target areas, distinguishing itself from conventional guidance approaches through its reliance on visual data for precise spatial decision-making.

160

Publications

7.7K

Citations

502

Authors

190

Institutions

Publications per year

2017–2026

51

Authors

502

  1. JF
    John F. Reid

    University of Illinois Urbana-Champaign, United States

    7 publications · 291 citations

    7

    h-index

  2. ED
    Ernst D. Dickmanns

    Universität der Bundeswehr München, Germany

    4 publications · 245 citations

    4

    h-index

  3. EB
    E.R. Benson

    University of Delaware, United States

    3 publications · 141 citations

    3

    h-index

  4. SW
    Stephen W. Searcy

    Texas A&M University, United States

    3 publications · 131 citations

    3

    h-index

  5. MÁ
    Miguel Á. Salichs

    Universidad Carlos III de Madrid, Spain

    2 publications · 585 citations

    2

    h-index

1–5 of 502

Venues

  1. Computers and Electronics in Agriculture

    7 publications · 412 citations

    7

    h-index

  2. Assembly Automation

    4 publications · 135 citations

    4

    h-index

  3. Transactions of the ASAE

    4 publications · 159 citations

    4

    h-index

  4. 4

    h-index

  5. Control Engineering Practice

    2 publications · 36 citations

    2

    h-index

1–5