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In the smart transportation system, vehicle detection is crucial. Additionally, it has a big impact on a lot of other things including advanced driver assistance systems, fleet management, asset tracking, surveillance and security, autonomous cars and robotics, and traffic monitoring and management. Contributes significantly to automation, safety, security, and traffic efficiency, among other facets of contemporary life. This project’s main goal is to investigate the creation and use of neural network models for the prediction of vehicle models and the detection of cars in photos. Several common network models, including CNN (Convolutional Neural Network Features), the Classification Model, and Fuzzy Logic, have been used in these training and classification trials. This approach aims to provide a more accurate vehicle classification.

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Fuzzy Logic and Integrated Deep Learning (DL) Solution for Precise Vehicle Detection and Classification

  • 章节

  • 发表日期：

    2025年

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  • Khushwant Singh,
  • Mohit Yadav,
  • Yudhvir Singh,
  • Daksh Khurana,
  • Binesh Kumar

摘要

In the smart transportation system, vehicle detection is crucial. Additionally, it has a big impact on a lot of other things including advanced driver assistance systems, fleet management, asset tracking, surveillance and security, autonomous cars and robotics, and traffic monitoring and management. Contributes significantly to automation, safety, security, and traffic efficiency, among other facets of contemporary life. This project’s main goal is to investigate the creation and use of neural network models for the prediction of vehicle models and the detection of cars in photos. Several common network models, including CNN (Convolutional Neural Network Features), the Classification Model, and Fuzzy Logic, have been used in these training and classification trials. This approach aims to provide a more accurate vehicle classification.