Machine Learning Based Theft Detection Using Yolo Object Detection

Authors

  • Swati Khadse  Department Computer Science and Engineering, Gurunanak Institude of Enginnering and Technology, Maharashtra, India
  • Babli Nandanwar  Department Computer Science and Engineering, Gurunanak Institude of Enginnering and Technology, Maharashtra, India
  • Ashwini Kirme  Department Computer Science and Engineering, Gurunanak Institude of Enginnering and Technology, Maharashtra, India
  • Taiksha Bagde  Department Computer Science and Engineering, Gurunanak Institude of Enginnering and Technology, Maharashtra, India
  • Vijaya Kamble  Professor Department Computer Science and Engineering, Gurunanak Institude of Engineering and Technology, Maharashtra, India

Keywords:

Machine learning, Image Processing, Yolo, Tensor Flow.

Abstract

Theft is a common criminal activity that is prevailing over the years and is increasing day by day. To tackle this problem many surveillance systems have been introduced in the market. Some are simply based on video surveillance monitored by a human while some are AI-based capable of detecting suspicious activity and raising an alarm. However, none of them are intelligent enough to identify what kind of suspicious activity is being carried out and what kind of protective measures should be taken in real-time. This blog presents the design of an effective surveillance system using machine learning techniques.

References

  1. Chengji Liu, Yufan Tao, jaiwei Liang “Object Detection Based on YOLO Network” 2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC) 10.1109/ITEOC.2018.874064
  2. R. Sujeetha, Vaibhav Mishra “Object Detection and Tracking using Tensor Flow” ISSN: 2277-3878, Volume-8, Issue-1, May 2019
  3. Kislay Keshri – “Object Detection Tutorial in Tensor Flow: Real- Time Object Detection”
  4. Tanvir Ahmad – “Object Detection Through Modified YOLO Neural Network” International Journal of Engineering Research & Technology    (IJERT), volume 2020 |Article ID 8403262

International Journal of Scientific Research in Science and Technology

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Published

2022-02-28

Issue

Volume 9, Issue 1, January-February-2022

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Swati Khadse, Babli Nandanwar, Ashwini Kirme, Taiksha Bagde, Vijaya Kamble "Machine Learning Based Theft Detection Using Yolo Object Detection" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 9, Issue 1, pp.117-120, January-February-2022.