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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    Titel :

    Lane-Based Vehicle Recognition Using Deep Learning Models


    Weitere Titelangaben:

    Lect.Notes Social.Inform.


    Beteiligte:
    Huynh, Hiep Xuan (Herausgeber:in) / Pham, Congduc (Herausgeber:in) / Duong-Trung, Nghia (Herausgeber:in) / Mien, Doan Phuoc (Autor:in) / Vu, Tran The (Autor:in)

    Kongress:

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



    Erscheinungsdatum :

    10.08.2025


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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