Improved algorithm for pedestrian detection from the perspective of UAV

For the pedestrian detection task from the perspective of unmanned aerial vehicle (UAV), the detection accuracy is low due to the effectiveness, complex background, large scale change and uneven distribution of detection targets. This study proposes an improved Yolov8x algorithm based on normalized Gaussian Wasserstein distance, which improves the accuracy, recall rate and mAP of pedestrian detection by 5%, 4% and 6%, respectively.