POLD-YOLO: A Lightweight YOLO11-Based Algorithm for Insulator Defect Detection in UAV Aerial Images

What are the main findings?

• Small target detection capability is significantly enhanced in the proposed YOLO-based method through the integration of several key innovations: depthwise and full-dimensional dynamic convolutions within a C3K2-PFCGLU module, adaptive downsampling via an OD-ADown module, a lightweight shared convolutional detection head (LSCD-Head) employing global average pooling, and a Focaler-MPDIoU loss that introduces the minimum point distance to focus on different regression samples.