SDY-YOLOV8n: research on improved small target detection algorithm based on UAV images

A UAV recognition algorithm developed using improved YOLOV8 (SLD-YOLOV8n) is proposed in this paper, To enhance the ability of multi-scale feature extraction, the proposed algorithm utilizes the LSKA attention mechanism to improve the structure of the SPPF; replaces the conv in the backbone with the SPD Conv, which increases the number of channels to save more image feature information; To tackle the disparity between simple and difficult samples, the proposed algorithm utilizes the SLideLoss classification loss function; in the detection head part, the Detect_DyHead detection head is used to improve the detection ability of the basic for different sized targets and to improve the robustness of the detection. The SDY-YOLOV8n technique has a better performance on the DIOR dataset , which improves 1.9 percentage points in mAP50 accuracy over the original YOLOv8n algorithm.