Computer Vision Systems and Methods for Vehicle Damage Detection with Reinforcement Learning

A non-transitory computer readable medium having instructions stored thereon for vehicle damage detection by a computer vision system which, when executed by a processor, causes the processor to carry out the steps of:

• generating a dataset,
• training a neural network with a plurality of images of the dataset to learn to detect damage to a vehicle present in an image of the dataset and to classify a location of the detected damage and a severity of the detected damage utilizing segmentation processing, and
• detecting the damage to the vehicle and classifying the location of the detected damage and the severity of the detected damage by the trained neural network,
• wherein the location of the detected damage is at least one of a front, a rear or a side of the vehicle and the severity of the detected damage is based on predetermined damage sub-classes.