A method, system and equipment for detecting and counting brown spot disease in rice.

Abstract

This invention relates to the field of crop breeding, and in particular to a method for detecting and counting brown spot disease in rice. The technical solution includes: improving the YOLOv8 model by introducing the C2f-EFA module, the ASFPN module, the WSIoU loss function, and the TADHead detection head to optimize model performance, achieving efficient and accurate detection and counting of brown spot disease in rice, improving the accuracy and efficiency of brown spot disease detection and counting, and providing technical support for rice disease analysis. Specifically, the C2f-EFA module enhances the ability to express the features of brown spot lesions and diseased leaves, significantly reducing the number of parameters and computational complexity, making it suitable for resource-constrained brown spot detection scenarios; the ASFPN module effectively improves the model's ability to detect brown spot lesions and diseased leaves, making it suitable for scenarios with large scale differences, complex backgrounds, and small lesions; the TADHead detection head enhances the model's generalization ability for brown spot detection, strengthens the detection accuracy of brown spot lesions and diseased leaves, and ensures robustness under complex backgrounds or low contrast conditions; the WSIoU loss function significantly improves the accuracy of lesion and diseased leaf localization.

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