关键词: 图像处理, 深度学习, 卷积神经网络, 人脸检测, 人脸识别

Abstract: In view of the problems of missing signatures and signing for someone else in the RFID conference registration system，a face recognition algorithm was used to assist the registration system to solve the above-mentioned problem of mismatching of person and identification. Due to the limited memory of the hardware equipment of the conference registration system，a lightweight network model was needed，so that the MobileNetV2 network was considered as the research object of the face recognition algorithm. Since the high real-time performance and accuracy required by the registration system，it is necessary to improve the recognition speed and accuracy of the algorithm，so the MobileNetV2 network was improved. In order to further improve the generalization ability of face recognition and the convergence speed of the algorithm，the adaptive scaling cosine loss function AdaCos was used to replace the Arcface loss function to perform network training. Experimental results show that the designed lightweight face recognition algorithm achieves good results in terms of recognition accuracy，recognition speed and algorithm model size. The algorithm can fully meet the requirements of registration system without losing accuracy.

Key words: image processing, deep learning, convolutional neural network, face detection, face recognition