Traffic Signs Detection and Recognition System in Snowy Environment Using Deep Learning

A fully autonomous car does not yet exist. But the vehicles have continued to gain in range recent years. The main reason? dazzling progress made artificial intelligence, particular by specific algorithms, known as machine learning. These example-based learning methods are used for recognizing objects photos. algorithms developed detection and identification must respond robustly various disturbances observed take into account variability signs’ appearance. Variations illumination generate changes apparent color, shadows, reflections, or backlighting. Besides, geometric distortions rotations may appear depending on viewing angle panels’ scale. Their appearance also vary their state of wear possible dirt, damage. In this work, improve accuracy classification sign road partially covered snow, we use Fast Region-based Convolutional Network method (Fast R-CNN) model. To train model, collect an image dataset composed multi-class signs. Our model can simultaneously a nearly real-time.