This research work aims to perform object detection by using the You Look Only Once (YOLO) method. This method is much efficient to the existing models in terms of speed and performance. Some of the algorithms do not scan all the regions in single forward propagation but in YOLO, the algorithm analyzes the entire image by predicting binding boxes using convolutional neural network and class opportunities. YOLO performs faster when compared to other algorithms.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Real Time Object Detection using YOLO Algorithm


    Beteiligte:


    Erscheinungsdatum :

    01.12.2022


    Format / Umfang :

    367599 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    YOLO-ESFM: A multi-scale YOLO algorithm for sea surface object detection

    Wei, Maochun / Chen, Keyu / Yan, Fei et al. | Elsevier | 2025

    Freier Zugriff

    Waiting Time Estimation of Hydrogen-Fuel Vehicles with YOLO Real-Time Object Detection

    Fikri, Rifqi Muhammad / Kim, Byungwook / Hwang, Mintae | Springer Verlag | 2019


    A Real-Time Malaysian Traffic Sign Recognition Using YOLO Algorithm

    Mangshor, Nur Nabilah Abu / Paudzi, Nurul Paudziah Aida Mohd / Ibrahim, Shafaf et al. | Springer Verlag | 2021


    A Real-Time Malaysian Traffic Sign Recognition Using YOLO Algorithm

    Abu Mangshor, Nur Nabilah / Paudzi, Nurul Paudziah Aida Mohd / Ibrahim, Shafaf et al. | British Library Conference Proceedings | 2022


    YOLO Object Detection Algorithm with Hybrid Atrous Convolutional Pyramid

    Wang, Hui / Wang, Zhiqiang / Yu, Lijun et al. | British Library Conference Proceedings | 2022