You Only Look Once(YOL O) Object Detection with COCO using Machine Learning
Concept Neural Network (CNN) is employed in YOLO (You Only Look Once) algorithm to detect Objects in real-time to achieve the requirements of latest object detection of the advanced world.
Abstract
Object Detection is the most important mission in computer imaginative and prescient within the latest times. It is widely used in Autonomous driving, wildlife protection, security system, etc. The orthodox processing objects of the image have various shortcomings in order to achieve the requirements of the latest current improved high level computer vision needs. With the recent advancement in deep neural network and various different image processing and machine learning algorithms, now things are quite comfortable to go with object detection, classification and many more. In this paper, Convolution Neural Network (CNN) is employed in YOLO (You Only Look Once) algorithm to detect Objects in real-time. Object Detection includes various approaches inclusive of fast R-CNN, Retina-Net, and Single-shot Multi Box Detector (SSD). YOLO is used in real-time image processing at a larger extend because of its great performance with superior speed and accuracy over the aforementioned object detection techniques. In this project,COCO model is used with YOYO algorithm in order to achieve the requirements of latest object detection of the advancedworld.