Real-time Large Scale Traffic Sign Detection

Automatic traffic sign detection and recognition has achieved good results using convolutional neural networks. Novel architectures are still being proposed in order to improve accuracy of detection and segmentation of traffic sings. In this paper, we are examining the possibility for traffic sign detection and recognition in real-time. For that purpose, we employed a novel YOLOv3 architecture, which has been proven to be fast and accurate method for object detection. It was shown that real-time detection can be achieved, even on HD images, with mAP above 88%.