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Hardware and Software Support for Insect Pest Management

Author

Listed:
  • Jozsef Suto

    (Department of IT Systems and Networks, University of Debrecen, 4028 Debrecen, Hungary
    Department of IT, Eszterházy Károly Catholic University, 3300 Eger, Hungary)

Abstract

In recent years, the achievements of machine learning (ML) have affected all areas of industry and it plays an increasingly important role in agriculture as well [...]

Suggested Citation

  • Jozsef Suto, 2023. "Hardware and Software Support for Insect Pest Management," Agriculture, MDPI, vol. 13(9), pages 1-2, September.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:9:p:1818-:d:1241308
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    References listed on IDEAS

    as
    1. Jozsef Suto, 2022. "Codling Moth Monitoring with Camera-Equipped Automated Traps: A Review," Agriculture, MDPI, vol. 12(10), pages 1-18, October.
    2. Dana Čirjak & Ivan Aleksi & Darija Lemic & Ivana Pajač Živković, 2023. "EfficientDet-4 Deep Neural Network-Based Remote Monitoring of Codling Moth Population for Early Damage Detection in Apple Orchard," Agriculture, MDPI, vol. 13(5), pages 1-20, April.
    3. Mustapha Abubakar & Bhupendra Koul & Krishnappa Chandrashekar & Ankush Raut & Dhananjay Yadav, 2022. "Whitefly ( Bemisia tabaci ) Management (WFM) Strategies for Sustainable Agriculture: A Review," Agriculture, MDPI, vol. 12(9), pages 1-39, August.
    4. Tiago Domingues & Tomás Brandão & Ricardo Ribeiro & João C. Ferreira, 2022. "Insect Detection in Sticky Trap Images of Tomato Crops Using Machine Learning," Agriculture, MDPI, vol. 12(11), pages 1-19, November.
    Full references (including those not matched with items on IDEAS)

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