Object Detection in Visible and Infrared missile borne fusion image

At present, common object detection methods for missile borne images often perform poorly. Because the experimental data of missile borne images is difficult to obtain, the target is small, and the imaging environment is complex and random, it is a challenge to build an appropriate object detection model for such missile borne images. Based on the classic YOLOv5, the paper constructs an aerial platform image target detection model YOLO v5mb, which is suitable for missile borne images. The model can accurately detect targets in single-mode visible or infrared missile borne images. In addition, the fusion layer architecture in YOLO v5mb makes it suitable for multimode visible and infrared missile borne fusion images object detection.