Comparative Analysis of Object Detection Algorithms for Pothole Recognition on Roads and Highways

This work presents a comparative analysis using the mAP metric of the YOLOv7 and SSD algorithms applied to the field of computer vision. The comparison is performed through the detection of potholes on highways and roads. In works defended by other authors, both techniques are considered for applications in computer vision. In this study, both models achieved promising results in pothole detection; however, it is observed that the YOLOv7 model reached an mAP metric of 80%, while the SSD model obtained an mAP of 73%. Thus, the results indicate that YOLOv7 is more efficient and accurate in pothole detection in this specific context.