Investigation of an Efficient Multi-Class Cotton Leaf Disease Detection Algorithm That Leverages YOLOv11

Cotton leaf diseases can lead to substantial yield losses and economic burdens. Traditional detection methods are challenged by low accuracy and high labor costs. This research presents the ACURS-YOLO network, an advanced cotton leaf disease detection architecture developed on the foundation of YOLO...

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Bibliografische gegevens
Hoofdauteurs: Fangyu Hu, Mairheba Abula, Di Wang, Xuan Li, Ning Yan, Qu Xie, Xuedong Zhang
Formaat: Artikel
Taal:Engels
Gepubliceerd in: MDPI AG 2025-07-01
Reeks:Sensors
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Online toegang:https://www.mdpi.com/1424-8220/25/14/4432
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