Automakers are working on merging Advanced Driving Assistance Systems (ADAS) with artificial intelligence and computer vision to reduce the number of fatalities and accidents brought on by distracted driving. One of the primary criteria for autonomous vehicles and the majority of ADAS is the capacity to perceive and comprehend all static and moving objects surrounding a vehicle in a variety of driving and environmental situations. Artificial intelligence may fulfill the current promise to supply safe ADAS in contemporary vehicles (AI). To support ADAS, this article demonstrated automated traffic sign identification for the Indian Traffic Scenario. The traffic signs are categorized into their superclass and subclasses. Deep learning is employed for feature extraction and ensemble learning for classification. The testing results using databases of Indian traffic signs demonstrated that the proposed method performed on par with state-of-the-art techniques and that the processing effectiveness of the entire recognition process was also increased.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Traffic Sign Recognition Using Hybrid Deep Ensemble Learning for Advanced Driving Assistance Systems


    Beteiligte:
    Utane, Akshay S. (Autor:in) / Mohod, S. W. (Autor:in)


    Erscheinungsdatum :

    25.10.2022


    Format / Umfang :

    884556 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Research on Traffic Sign Detection and Recognition System Using Deep Ensemble Learning

    Wang, Lung-Jen / Suwattanapunkul, Taweelap / Thalauy, Jarinya et al. | IEEE | 2024


    Robust traffic sign recognition and tracking for Advanced Driver Assistance Systems

    Zheng, Zhihui / Zhang, Hanxizi / Wang, Bo et al. | IEEE | 2012


    Traffic Sign Recognition and Voice-Activated Driving Assistance Using Raspberry Pi

    Kavitha, C. / Thamaraikannan, V. / Vigneshkumar, M. et al. | IEEE | 2023


    Encrypted Transfer of Traffic Sign Information for Advanced Driving Assistance Systems Using Invisible Security Patches

    Karaaslan, Enes / Zakaria, Mahta / Ercan, Tolga et al. | Transportation Research Record | 2022


    Traffic Sign Recognition with Faster RCNN and RPN for Advanced Driver Assistance Systems

    K R, SARUMATHI / M, DHIVYASHREE / R S, VISHNU DURAI | IEEE | 2021