Object Detection Using YOLO- You Look Only Once

Abstract

To classify and locate n number of object in the image is major aspect of object detection. It is mostly in relevance to the computer vision. In the field of computer vision, it is been considered to be one of the difficult and challenging tasks. Day by day, by the evaluation of deep learning algorithms it became more fast, accurate and robust. In order to make algorithms efficient ,needs to consider both precision and computation time. To implement object detection for real time application it needs the computational time per image should be in milli seconds. Also to execute it more accurately and faster many deep learning techniques has came into the picture. The output of this object detection is in variable size, since n number of object has to be detected also from different different images. In this Report we have discussed about different object detection algorithms and their comparison in terms of mAP(Mean Average Precision) and computation time. Also the implementation of YOLO Algorithm. In this what are the factors that needs to be taken in to account while using algorithm for real time application.