Blind-Spot Collision Detection System for Commercial Vehicles Using Multi Deep CNN Architecture.

Muzammel, Muhammad; Yusoff, Mohd Zuki; Saad, Mohamad Naufal Mohamad; Sheikh, Faryal; Awais, Muhammad Ahsan

Muzammel, Muhammad; Yusoff, Mohd Zuki; Saad, Mohamad Naufal Mohamad; Sheikh, Faryal; Awais, Muhammad Ahsan.

Afiliación

Muzammel M; Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.
Yusoff MZ; Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Université Paris-Est Créteil (UPEC), 94400 Vitry-sur-Seine, France.
Saad MNM; Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.
Sheikh F; Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.
Awais MA; Department of Management Sciences, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan.

Sensors (Basel) ; 22(16)2022 Aug 15.

Article en En | MEDLINE | ID: mdl-36015850

Asunto(s)

Vehículos a Motor; Redes Neurales de la Computación; Automóviles

Palabras clave

blind spot collision detection for buses; blind spot vehicle detection; collision detection system; deep CNN architecture; deep learning model; heavy vehicle safety; road safety

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Redes Neurales de la Computación / Vehículos a Motor Tipo de estudio: Clinical_trials / Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Malasia Pais de publicación: Suiza

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