Analytical Study on Object Detection using Yolo Algorithm


Authors : Dawn Wilson; Dr. Manusankar C; Dr. Prathibha P H

Volume/Issue : Volume 7 - 2022, Issue 8 - August

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3AWmpqK

DOI : https://doi.org/10.5281/zenodo.7036535

Abstract : - Object detection is a technique that allows detecting and locating objects in videos and images. Object detection is widely used to count objects in a scene, track their precise locations and accurately label the objects. It seeks to answer what is the object? and Where is it? . Object detection adopts various approaches such as fast R-CNN, Retina-Net, Single Shot MultiBox Detector (SSD) and YOLO. Among these, YOLO is the most powerful algorithm for object detection and as well as suited for real-time scenarios. It is popular because of its accuracy and speed. YOLO uses Neural networks to provide object detection.

Keywords : YOLO, Neural Networks, CNN, Object detection.

- Object detection is a technique that allows detecting and locating objects in videos and images. Object detection is widely used to count objects in a scene, track their precise locations and accurately label the objects. It seeks to answer what is the object? and Where is it? . Object detection adopts various approaches such as fast R-CNN, Retina-Net, Single Shot MultiBox Detector (SSD) and YOLO. Among these, YOLO is the most powerful algorithm for object detection and as well as suited for real-time scenarios. It is popular because of its accuracy and speed. YOLO uses Neural networks to provide object detection.

Keywords : YOLO, Neural Networks, CNN, Object detection.

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe