The Object Detection in Remote Sensing Images Based on Improved YOLO11 with LDConv

The YOLO series of object detection algorithms have been constantly updated in recent years, the latest YOLO algorithm has been updated to YOLO11, which can not only detect objects more accurately, but also detect sloping objects. Based on the newly released YOLO11-OBB algorithm, this paper improved the YOLO11-OBB algorithm on the remote sensing image dataset of Tianzhi Cup Competition held in this year, combined with a newly released LDConv algorithm, and finally trained the improved algorithm, which can improve the mAP of the YOLO11-OBB-N algorithm by 3.7% and the number of parameters is reduced by 4.5%, enabling more accurate and less computationally intensive object detection.