Traffic Offender Detection System Using Deep Learning Approach

Authors

  • Dr. Praveen Blessington Thummalakunta  Professor, Department of Information Technology, Zeal College of Engineering and Research, Pune, Maharashtra, India.
  • Manav More  Department of Information Technology, Zeal College of Engineering and Research, Pune, Maharashtra, India
  • Rhutuja Kakade  Department of Information Technology, Zeal College of Engineering and Research, Pune, Maharashtra, India
  • Omkar Nagare  Department of Information Technology, Zeal College of Engineering and Research, Pune, Maharashtra, India
  • Rutuja Sawant  Department of Information Technology, Zeal College of Engineering and Research, Pune, Maharashtra, India

DOI:

https://doi.org/10.32628/IJSRST5241118

Keywords:

Vehicle Detection, Helmet Detection, Crosswalk Inversion, Traffic Plate Recognition.

Abstract

The issue of monitoring and controlling traffic violations has become a significant concern in India, primarily due to the large population, increasing number of commuters, ineffective traffic signal management, and the behaviour of riders. Relying solely on physical traffic police for monitoring has proven insufficient in handling such high traffic volumes while simultaneously tracking violations. The issue of monitoring and controlling traffic violations has become a significant concern in India, primarily due to the large population, increasing number of commuters, ineffective traffic signal management, and the behaviour of riders. Relying solely on physical traffic police for monitoring has proven insufficient in handling such high traffic volumes while simultaneously tracking violations.

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Published

2024-02-29

Issue

Section

Research Articles

How to Cite

[1]
Dr. Praveen Blessington Thummalakunta, Manav More, Rhutuja Kakade, Omkar Nagare, Rutuja Sawant "Traffic Offender Detection System Using Deep Learning Approach" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 11, Issue 1, pp.63-72, January-February-2024. Available at doi : https://doi.org/10.32628/IJSRST5241118