CAR DETECTION IN LIVE SURVEILLANCE USING DEEP LEARNING

  • Unique Paper ID: 147275
  • Volume: 5
  • Issue: 6
  • PageNo: 338-341
  • Abstract:
  • With the increase in number of vehicles in the country vehicle detection is an important in road traffic management system. Different traffic parameters such as vehicle speed, count, traffic movement rate, travelling time, traffic congestion level can be calculated by using vehicle detection method. The results obtained from traffic parameters can be applied for vehicle tracking, vehicle classification, parking area monitoring, road traffic monitoring and management etc. The main objective of this project is to decrease the deaths caused by accident occurring because over speeding ensuring public safety and also a building a better system for managing the traffic on the roads. The aim of this paper is to develop a system that can detect the vehicle, classify and count the vehicle and detect speed of the vehicle on city roads using deep learning technology. A prototype system is developed and tested.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{147275,
        author = {Shrey Gupta and Vandana Choudhary},
        title = {CAR DETECTION IN LIVE SURVEILLANCE USING DEEP LEARNING },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {5},
        number = {6},
        pages = {338-341},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=147275},
        abstract = {With the increase in number of vehicles in the country vehicle detection is an important in road traffic management system. Different traffic parameters such as vehicle speed, count, traffic movement rate, travelling time, traffic congestion level can be calculated by using vehicle detection method. The results obtained from traffic parameters can be applied for vehicle tracking, vehicle classification, parking area monitoring, road traffic monitoring and management etc. The main objective of this project is to decrease the deaths caused by accident occurring because over speeding ensuring public safety and also a building a better system for managing the traffic on the roads.  The aim of this paper is to develop a system that can detect the vehicle, classify and count the vehicle and detect speed of the vehicle on city roads using deep learning technology. A prototype system is developed and tested. },
        keywords = {Deep Learning, Heatmap, OpenCV, ROI, SSD Model, TensorFlow},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 5
  • Issue: 6
  • PageNo: 338-341

CAR DETECTION IN LIVE SURVEILLANCE USING DEEP LEARNING

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