“In the field of object detection, a lightweight small object detection algorithm based on YOLOv8s improvement is proposed to address the challenge of detecting small aerial target images. The experimental results show that the proposed algorithm achieves mAP50 and mAP50:95 of 41.4% and 24.9%, respectively, on the Visdrone dataset. Compared with the original YOLOv8s algorithm, the accuracy is improved by 1.6% and 1.3%, and the parameter and computational complexity are reduced by 36.8% and 42.8%, respectively.”