In view of the mutual interference between student distribution, perspective, scale and target in the classroom environment and the uncertainty of lighting, face detection in the classroom is faced with a large error. Through in-depth study of YOLOV5s architecture, CBAM attention mechanism was embedded into SPPF module of the pattern skeleton, and C3 module was transformed into C2. The accuracy rate of this model was $70.1 \%$, the recall rate was $66.3 \%$, and the average accuracy was $66.9 \%$, which was $4 \%$ higher than the average accuracy of the original model.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Face recognition in images based on deep learning


    Beteiligte:
    Li, Xin (Autor:in)


    Erscheinungsdatum :

    23.10.2024


    Format / Umfang :

    660466 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    3D Face Recognition Based on Deep Learning

    Luo, Jing / Hu, Fei / Wang, Ruihuan | British Library Conference Proceedings | 2019


    Sketch face Recognition using Deep Learning

    Rubeena / Kavitha, E. | IEEE | 2021


    Face recognition in hyperspectral images

    Zhihong Pan, / Healey, G.E. / Prascad, M. et al. | IEEE | 2003


    Face Recognition in Hyperspectral Images

    Pan, Z. / Healey, G. / Prasad, M. et al. | British Library Conference Proceedings | 2003


    Text Recognition from Images Using Deep Learning Techniques

    Narendra Kumar Rao, B. / Pranitha, Kondra / Ranjana et al. | Springer Verlag | 2022