Real-Time Detection and Analysis of Vehicles and Pedestrians using Deep Learning

arXiv:2404.08081v1 Announce Type: new
Abstract: Computer vision, particularly vehicle and pedestrian identification is critical to the evolution of autonomous driving, artificial intelligence, and video surveillance. Current traffic monitoring systems confront major difficulty in recognizing small objects and pedestrians effectively in real-time, posing a serious risk to public safety and contributing to traffic inefficiency. Recognizing these difficulties, our project focuses on the creation and validation of an advanced deep-learning framework capable of processing complex visual input for precise, real-time recognition of …

abstract analysis and analysis artificial artificial intelligence arxiv autonomous autonomous driving computer computer vision cs.cv current deep learning detection driving evolution identification intelligence major monitoring objects pedestrian pedestrians public public safety real-time risk safety small surveillance systems traffic type vehicles video video surveillance vision