BL-YOLOV11: An improved model for road defect detection

In the modern automotive industry, the demand for road crack detection is increasing, but the current methods either over-pursuing the lightweight, which leads to the performance unchanged or even decreased or over-pursuing the performance index, and do not consider the limitation of computational resources, this paper proposes a model BL-YOLOV11, which achieves a balance between the performance and the improvement of the utilization of computational resources, and the model is better than the original model YOLOV11. In terms of performance, YOLOV11 improves Precision by 5%, Recall by 4%, and mAP@50 and mAP@50:90 by 4% and 2%, respectively, with only a 3% increase in computational resources, which is an effective improvement in balancing computational efficiency and performance.