Face Recognition System Based on Deep Residual Network

被引:0
|
作者
Liang, Juan [1 ]
Zhao, Haoyu [2 ]
Li, Xingqian [1 ]
Zhao, Hongwei [1 ]
机构
[1] JILIN Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China
[2] JILIN Univ, Editorial Dept Journal, Changchun 130012, Peoples R China
关键词
Residual Network; Face Recognition; Android; !text type='Python']Python[!/text; SL4A;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
With the development of social science and technology, people's awareness of the safety of life gradually high, face recognition technology has entered people's lives. This paper designs a face recognition system based on the depth residual network. This system is implemented in both PC and Android. the PC terminal can add voice broadcast function, timely and effectively remind and prevent should be adopted when "danger" appears. The implementation of the Android mobile terminal is achieved by combining the Android and Python harmoniously through the platform of the Python scripting language provided by SL4A. Face recognition in the Android mobile side can be used for identity security authentication, mobile payment and other convenient operation, greatly increased the ease of operation of the system to make up for the PC side to carry inconvenient enough, the experiment proved that the face recognition technology Embedded into the Android terminal has a good recognition effect.
引用
收藏
页码:363 / 367
页数:5
相关论文
共 50 条
  • [1] Self Residual Attention Network For Deep Face Recognition
    Ling, Hefei
    Wu, Jiyang
    Wu, Lei
    Huang, Junrui
    Chen, Jiazhong
    Li, Ping
    IEEE ACCESS, 2019, 7 : 55159 - 55168
  • [2] White Blood Cells Recognition System Based on Deep Residual Network
    Almotairi, Sultan
    Shahin, A., I
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2019, 19 (10): : 90 - 98
  • [3] Face recognition based on improved residual neural network
    Chen Zhenzhou
    Ding Pengcheng
    PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 4626 - 4629
  • [4] Facial Expression Recognition System Based on Deep Residual Fusion Neural Network
    Wang, Haonan
    Ding, Junhang
    Wang, Fan
    Ma, Zhe
    PROCEEDINGS OF 2019 CHINESE INTELLIGENT AUTOMATION CONFERENCE, 2020, 586 : 138 - 144
  • [5] Research on Face Recognition System based on Embedded Processor and Deep Neural Network
    Du, Bowen
    Guo, Xiaoxia
    Chen, Yangyang
    2018 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND PATTERN RECOGNITION (AIPR 2018), 2018, : 11 - 14
  • [6] Face Recognition Based on Improved Residual Network and Channel Attention
    Zeng, Jingfang
    Li, Jieyu
    Feng, Linlang
    AUTOMATIC CONTROL AND COMPUTER SCIENCES, 2022, 56 (05) : 383 - 392
  • [7] Face Recognition Based on Improved Residual Network and Channel Attention
    Jieyu Jingfang Zeng
    Linlang Li
    Automatic Control and Computer Sciences, 2022, 56 : 383 - 392
  • [8] Fish Recognition Based on Deep Residual Shrinkage Network
    Cheng, Long
    He, Chengwan
    2021 4TH INTERNATIONAL CONFERENCE ON ROBOTICS, CONTROL AND AUTOMATION ENGINEERING (RCAE 2021), 2021, : 36 - 39
  • [9] Radar Waveform Recognition based on Deep Residual Network
    Qin, Xin
    Zha, Xiong
    Huang, Jie
    Luo, Liping
    PROCEEDINGS OF 2019 IEEE 8TH JOINT INTERNATIONAL INFORMATION TECHNOLOGY AND ARTIFICIAL INTELLIGENCE CONFERENCE (ITAIC 2019), 2019, : 892 - 896
  • [10] Facial expression recognition based on deep residual network
    Qu, Junsuo
    Zhang, Ruijun
    Zhang, Zhiwei
    Pan, Jeng-Shyang
    Journal of Computers (Taiwan), 2020, 31 (02): : 12 - 19