Accident Detection Using Mask R-CNN

Abstract

Deep learning is an artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making. Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning and recognizing patterns from data that is unstructured or unlabeled. It is also known as deep neural learning or deep neural network. Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification. ConvNets have been successful in identifying faces, objects and traffic signs apart from powering vision in robots and self-driving cars. Consistently around the globe, an enormous number of individuals pass on from vehicle crash wounds. A large portion of the drivers are very much aware of the overall principles and security measures while driving yet it is just the laxity on their part, which causes mishaps and accidents. This paper helps in the detection of road accidents using the Mask R-CNN approach.