Image-based Pest Detection

Image-Based Pest Detection is a computational method that identifies and classifies pest species in agricultural environments by analyzing visual data captured through imaging technologies, distinguishing itself from other pest detection approaches through its reliance on digital image processing and pattern recognition techniques.

448

Publications

24K

Citations

1.8K

Authors

572

Institutions

Publications per year

2017–2026

369

Authors

1.8K

  1. CX
    Chengjun Xie

    Institute of Intelligent Machines, China

    13 publications · 1.1K citations

    13

    h-index

  2. RW
    Rujing Wang

    Institute of Intelligent Machines, China

    11 publications · 677 citations

    11

    h-index

  3. RL
    Rui Li

    Hefei Institutes of Physical Science, China

    8 publications · 430 citations

    8

    h-index

  4. JD
    Jianming Du

    University of Science and Technology of China, China

    8 publications · 246 citations

    8

    h-index

  5. SD
    Shifeng Dong

    Institute of Intelligent Machines, China

    7 publications · 504 citations

    7

    h-index

1–5 of 1.8K

Venues

  1. Computers and Electronics in Agriculture

    48 publications · 5.8K citations

    37

    h-index

  2. Frontiers in Plant Science

    28 publications · 2K citations

    19

    h-index

  3. Agriculture

    16 publications · 727 citations

    15

    h-index

  4. Ecological Informatics

    15 publications · 893 citations

    14

    h-index

  5. IEEE Access

    15 publications · 943 citations

    13

    h-index

1–5