MAD-YOLO: multi-dimensional attention and dynamic feature aggregation for UAV small object detection
The proposed MAD-YOLO, an efficient object detection framework aimed at enhancing small-object perception and multi-scale feature interaction in complex aerial scenes, adopts the existing mixed local channel attention mechanism and embeds it into the C2PSA architecture to enhance local-global feature representation.