A Lightweight Detection Model for Peanut Leaf Diseases

Peanut leaf disease detection in complex field environments faces two major challenges: distinguishing visually similar symptoms and identifying severely occluded lesions. This study presents YOLOv8-MSDH, a lightweight detection model built upon an improved YOLOv8 framework to address these issues. Four architectural enhancements are introduced. First, the MHSA attention mechanism is integrated to enhance sequential feature dependency modeling and suppress background noise. Second, the Slim-Neck