PTCDet: advanced UAV imagery target detection.

Object detection in drone aerial images is challenging due to the difficulty of small object detection and complex backgrounds. To address these issues, this paper proposes an improved object detection model, perception and target capture detector (PTCDet), to increase detection accuracy and robustness in complex scenes. Specifically, the proposed multiple feature extraction attention (MFEA) module significantly enhances the ability of the model to detect small objects through multidimensional feature map augmentation.

MPE-YOLO: enhanced small target detection in aerial imaging.

Aerial image target detection is essential for urban planning, traffic monitoring, and disaster assessment. However, existing detection algorithms struggle with small target recognition and accuracy in complex environments. To address this issue, this paper proposes an improved model based on YOLOv8, named MPE-YOLO.