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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 10, ISSUE 12, DECEMBER 2021

A Survey on Tool Tracking System

Darvish Davis, Anandhu Kumar, Alen Jhonson

DOI: 10.17148/IJARCCE.2021.101248

Abstract: Object detection refers to the capability of computers and other systems to locate objects present in an image and identify each of them. It has been widely used for face detection in security systems, for vehicle detection in driverless cars, and so on. Existing system performs numerous simpler and complex tasks like real world object detection from videos, concealed object detection…etc. This project focuses on detecting tools from a toolkit. Output achieved an accurate result up to the expectation.

Keywords: YOLO model, Comparer, Computer vision, Machine learning.

How to Cite:

[1] Darvish Davis, Anandhu Kumar, Alen Jhonson, “A Survey on Tool Tracking System,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2021.101248