Manuscript Number : SHISRRJ247267

Object Detection and Localization with YOLOv3

Authors(2) :-B. Rupadevi, J.Pallavi

Computer vision has become a vital field with many applications, ranging from autonomous vehicles to medical picture analysis, in the age of rapid technological growth. A Python-based project called Comprehensive Visual Understanding System (CVUS) aims to create a flexible framework for a range of computer vision tasks. Modern algorithms and approaches are integrated in this project to provide strong visual understanding skills. Picture preprocessing, feature extraction, object identification and recognition, picture classification, and semantic segmentation are some of the essential elements that make up CVUS. Together, these elements create a pipeline that allows for thorough visual analysis of both photos and movies. To efficiently implement these components, the project makes use of well-known Python libraries like scikit-learn, TensorFlow, PyTorch, and OpenCV.

Authors and Affiliations

B. Rupadevi
Associate Professor, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, Andhra Pradesh, India
J.Pallavi
Post Graduate, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, Andhra Pradesh, India

OpenCV, TensorFlow, PyTorch, Deep Learning, Computer Vision, Python, Image Processing, Object Detection, Image Classification, and Semantic Segmentation.

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Publication Details

Published in : Volume 7 | Issue 2 | March-April 2024
Date of Publication : 2024-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 275-282
Manuscript Number : SHISRRJ247267
Publisher : Shauryam Research Institute

ISSN : 2581-6306

Cite This Article :

B. Rupadevi, J.Pallavi, "Object Detection and Localization with YOLOv3", Shodhshauryam, International Scientific Refereed Research Journal (SHISRRJ), ISSN : 2581-6306, Volume 7, Issue 2, pp.275-282, March-April.2024
URL : https://shisrrj.com/SHISRRJ247267

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