Object Detection for Autonomous Driving using YOLO [You Only Look Once] algorithm
This paper aims at aiding the field of autonomous driving by helping detect objects with the use of deep learning algorithms by using state-of-the-art algorithm YOLO (you only look once) to detect different objects that appear on the road and classified into the category that they belong to with the help of bounding boxes.
Abstract
The field of autonomous driving is going to be the face of the automobile industry very soon. The number of accidents that take place because of human error currently is very high and it can be slashed to a huge extent with the advent of autonomous driving. One of the primary prerequisites and a huge part of autonomous driving is dependent on object detection through computer vision, this paper aims at aiding towards the field of autonomous driving by helping detect objects with the use of deep learning algorithms. Research work used state-of-the-art algorithm YOLO (you only look once) to detect different objects that appear on the road and classified into the category that they belong to with the help of bounding boxes. The weights of the YOLO v4 is utilized to custom train our model to detect the objects and the data will be collected from the open images dataset using its OIDv4 toolkit.