Combining Image Restoration with Deep Detectors for Improved Target Detection in GPR

The target detection performance of GPR systems suffers from the noisy and partially lost data encountered in field studies. Since detection may benefit from the restoration of the data prior to detection procedure, a two-step approach is proposed. Firstly, the data is either denoised or recovered with networks appropriate to the nature of the task, then detection is performed by YOLOv5 or YOLOv10. Detection results obtained with the proposed approach confirm performance increase in terms of MAP values compared to the sole use of YOLOv5 or YOLOv10.