Vehicle Detection Algorithm Analysis

Authors

  • Abhishek Andure  Department of Information Technology, Nutan Maharashtra Institute of Engineering and Technology, Samarth Vidya Sankul Talegaon Dabhade, Puane, Maharashtra, India
  • Sakshi Pidurkar  Department of Information Technology, Nutan Maharashtra Institute of Engineering and Technology, Samarth Vidya Sankul Talegaon Dabhade, Puane, Maharashtra, India
  • Aditya Tarte  Department of Information Technology, Nutan Maharashtra Institute of Engineering and Technology, Samarth Vidya Sankul Talegaon Dabhade, Puane, Maharashtra, India
  • Swapnil Thorat  Department of Information Technology, Nutan Maharashtra Institute of Engineering and Technology, Samarth Vidya Sankul Talegaon Dabhade, Puane, Maharashtra, India
  • Sonali Patil  Department of Information Technology, Nutan Maharashtra Institute of Engineering and Technology, Samarth Vidya Sankul Talegaon Dabhade, Puane, Maharashtra, India
  • Nitin Dhawas  Department of Information Technology, Nutan Maharashtra Institute of Engineering and Technology, Samarth Vidya Sankul Talegaon Dabhade, Puane, Maharashtra, India

Keywords:

Computer vision, Intelligent transport system (ITS), Vehicle detection, Traffic management.

Abstract

Deep Learning is a rapidly advancing field that has the potential to revolutionize numerous areas of research and industry. One critical task within this domain is vehicle detection, which has practical applications in domains such as traffic management, public safety, and autonomous driving. Intelligent Transportation Systems (ITS) can be used for vehicle detection to count and track vehicles, detect incidents, and collect tolls. This helps improve traffic management, monitor flow and congestion, and better meet the needs of travellers and commuters, making transportation systems safer, more efficient, and effective. The goal of this task is to develop algorithms that can automatically detect and localize vehicles in images or videos by training Deep Learning models on labelled datasets of vehicle examples. Object detection using Deep Learning is a related task that involves identifying and localizing objects in images or videos. This task aims to automatically detect and classify objects within a scene and determine their precise location. Object detection using Deep Learning is beneficial in real-time applications such as surveillance systems, robotics, and self-driving cars, and can result in improved safety, efficiency, and automation across various domains.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-11-30

Issue

Volume 9, Issue 6, November-December-2023

Section

Research Articles

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How to Cite

[1]
Abhishek Andure, Sakshi Pidurkar, Aditya Tarte, Swapnil Thorat, Sonali Patil, Nitin Dhawas, " Vehicle Detection Algorithm Analysis" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 6, pp.144-154, November-December-2023.