Enhanced rock block detection method based on an improved YOLOv11

Rock block detection plays a crucial role in geological exploration, mine safety monitoring, and landslide early warning systems. Traditional rock block detection methods face challenges of insufficient accuracy and poor real-time performance in complex geological environments. This paper proposes an enhanced rock block detection method based on an improved YOLOv11, which integrates a lightweight Slim-Neck module into the YOLOv11 neck and replaces the original CIoU loss with SIoU loss, termed YOLOv11-SNS, achieving an optimized balance between detection accuracy and computational efficiency. Experimental results show that the improved YOLOv11-SlimNeck-SIoU model achieves an [email protected] of 0.684 under the same computational complexity, a 1.03% improvement over the baseline YOLOv11, with the F1 score increasing to 0.66, validating the effectiveness of the proposed method. This study provides an efficient and reliable technical solution for automatic rock block detection in complex geological environments.