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

- 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.

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