Optical Fiber Perimeter Intrusion Pattern Recognition Based on 1D-CNN

被引:0
|
作者
基于一维卷积神经网络的光纤周界入侵模式识别
机构
[1] Yu, Houdan
[2] Mi, Qiushi
[3] Zhao, Dong
[4] Xiao, Qian
来源
Xiao, Qian (ychunww@163.com) | 2021年 / Chinese Optical Society卷 / 50期
关键词
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [31] High-efficiency intrusion recognition by using synthesized features in optical fiber perimeter security system
    Huang Xiang-Dong
    Zhang Hao-Jie
    Liu Kun
    Ma Chun-Yu
    Liu Tie-Gen
    ACTA PHYSICA SINICA, 2017, 66 (12)
  • [32] A One-Dimensional Convolutional Neural Network (1D-CNN) Based Deep Learning System for Network Intrusion Detection
    Qazi, Emad Ul Haq
    Almorjan, Abdulrazaq
    Zia, Tanveer
    APPLIED SCIENCES-BASEL, 2022, 12 (16):
  • [33] Pattern Recognition of Grating Perimeter Intrusion Behavior in Deep Learning Method
    Li, Xianfeng
    Xu, Sen
    Hua, Xiaopeng
    SYMMETRY-BASEL, 2021, 13 (01): : 1 - 16
  • [34] Fast pattern recognition based on frequency spectrum analysis used for intrusion alarming in optical fiber fence
    Wang, Zhaoyong
    Pan, Zhengqing
    Ye, Qing
    Cai, Haiwen
    Qu, Ronghui
    Fang, Zujie
    Zhongguo Jiguang/Chinese Journal of Lasers, 2015, 42 (04):
  • [35] A Non-Contact Paraparesis Detection Technique Based on 1D-CNN
    Guan, Lei
    Hu, Fangming
    Al-Turjman, Fadi
    Khan, Muhammad Bilal
    Yang, Xiaodong
    IEEE ACCESS, 2019, 7 : 182280 - 182288
  • [36] FPGA Implementation of a BPSK 1D-CNN Demodulator
    Liu, Yan
    Shen, Yue
    Li, Li
    Wang, Hai
    APPLIED SCIENCES-BASEL, 2018, 8 (03):
  • [37] Rolling bearing fault diagnosis based on residual connection and 1D-CNN
    Zhao J.
    Zhao Z.
    Yang S.
    Zhendong yu Chongji/Journal of Vibration and Shock, 2021, 40 (10): : 1 - 6
  • [38] A Probabilistic Damage Identification Method Based on PZT Admittances and 1D-CNN
    Fu, Jing
    Wang, Dansheng
    2022 16TH SYMPOSIUM ON PIEZOELECTRICITY, ACOUSTIC WAVES, AND DEVICE APPLICATIONS, SPAWDA, 2022, : 572 - 576
  • [39] Attention based 1D-CNN for Mental Workload Classification using EEG
    Parveen, Fiza
    Bhavsar, Arnav
    PROCEEDINGS OF THE 16TH ACM INTERNATIONAL CONFERENCE ON PERVASIVE TECHNOLOGIES RELATED TO ASSISTIVE ENVIRONMENTS, PETRA 2023, 2023, : 739 - 745
  • [40] Prediction of Type II Diabetes Risk Based on XGBoost and 1D-CNN
    Wei, Zhang
    Qiang, Wu
    Yue, Xiuqing
    2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 5217 - 5222