Object Detection in Autonomous Vehicles
Razvan-Alexandru Bratulescu, Robert-Ionuţ Vătăşoiu, George Sucic, Sorina-Andreea Mitroi, Marius Vochin, Mari-Anais Sachian
Abstract
In the coming years, autonomous driving will be the primary focus of the automobile industry. The great majority of accidents are caused by human mistakes, and autonomous cars can help to lower this number significantly, thus improving road safety. Object identification plays a critical part in autonomous vehicle driving, and deep learning techniques are used to implement it. YOLO is one of the most common methods for recognizing and identifying things that emerge on the road. Its popularity has developed as a result of its superior performance in terms of speed, high accuracy, and learning capabilities when compared to other object recognition approaches such as Retina-Net, fast R- CNN, and Single-Shot MultiBox Detection (SSD).