SerpensGate-YOLOv8: an enhanced YOLOv8 model for accurate plant disease detection

Plant disease detection remains a significant challenge, necessitating innovative approaches to enhance detection efficiency and accuracy. This study proposes an improved YOLOv8 model, SerpensGate-YOLOv8, specifically designed for plant disease detection tasks. Key enhancements include the incorporation of Dynamic Snake Convolution (DySnakeConv) into the C2F module, which improves the detection of intricate features in complex structures, and the integration of the SPPELAN module, combining Spatial Pyramid Pooling (SPP) and Efficient Local Aggregation Network (ELAN) for superior feature extraction and fusion. Additionally, an innovative Super Token Attention (STA) mechanism was introduced to strengthen global…