An Improved YOLOv8 Model for Fish Classification and Disease Detection

Tóm tắt

Fish classification and disease detection are crucial for sustainable aquaculture, necessitating accurate and efficient vision models. This study
introduces FISH-YOLOV8, an enhanced YOLOv8 variant, incorporating: (1) SPD-Conv for optimized feature extraction and reduced
computational load; (2) BiFormer Attention for enhanced small object detection and occlusion management; (3) dynamic IoU-threshold NMS
to minimize false positives. This Article states that, evaluated on 15,162 images, FISH-YOLOV8 attains a mAP@50 of 0.990 and a
mAP@50:95 of 0.859, outperforming baseline YOLOv8 and advanced models such as YOLOv11, at 45 fps, supports effective real-time
aquaculture monitoring.