Design and research of face recognition intelligent charging cabinet based on deep learning

Peng Wang; Jianwei Li; Wenjing Qiao

doi:10.1117/12.3039721

28 August 2024 Design and research of face recognition intelligent charging cabinet based on deep learning

Peng Wang, Jianwei Li, Wenjing Qiao

Proceedings Volume 13251, Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024); 1325118 (2024) https://doi.org/10.1117/12.3039721
Event: 9th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024), 2024, Guilin, China

Abstract

The basic principles of deep learning face recognition are described, the concepts of deep learning in vivo detection and face recognition are introduced, and the Bottleneck features extracted by the VGG16 deep neural network are inputted into the fully connected network for face classification, and the employee face images are collected to construct a training dataset to train the deep learning model. Based on the Keras framework, the deep learning algorithm program is implemented, MySQL is used to establish the employee information, and the face recognition smart charging cabinet based on deep learning is applied and designed. This intelligent charging cabinet can realize face recognition, unified maintenance of equipment, and condition monitoring, which improves the informatization level of marketing mobile operation terminal equipment management.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Peng Wang, Jianwei Li, and Wenjing Qiao "Design and research of face recognition intelligent charging cabinet based on deep learning", Proc. SPIE 13251, Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024), 1325118 (28 August 2024); https://doi.org/10.1117/12.3039721

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