An essential part of intelligent transportation systems and traffic management is lane-based vehicle recognition. This paper introduces a real-time vehicle detection and classification system that uses deep learning models. Results from experiments show that the system can manage a variety of traffic situations, such as occlusions, high vehicle densities, and changing illumination conditions. The accuracy of traffic analysis is greatly increased by this lane-based detection system, which also supports real-time decision-making in traffic monitoring and offers insightful information for smart city applications.


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    Title :

    Lane-Based Vehicle Recognition Using Deep Learning Models


    Additional title:

    Lect.Notes Social.Inform.


    Contributors:

    Conference:

    International Conference on Smart Objects and Technologies for Social Good ; 2024 ; Can Tho, Vietnam December 19, 2024 - December 20, 2024



    Publication date :

    2025-08-10


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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