Deep Learning-Based Indoor Localization Using Adjacent Received Signal Strength and Domain Knowledge

被引:0
|
作者
Zhang, Guangyi [1 ]
Hou, Zhanwei [2 ]
Li, Yonghui [2 ]
Vucetic, Branka [2 ]
机构
[1] McGill University, Dept. Electrical and Computer Engineering, Montreal,QC, Canada
[2] University of Sydney, Dept. Electrical and Information Engineering, Sydney,NSW, Australia
关键词
Compendex;
D O I
暂无
中图分类号
学科分类号
摘要
Domain Knowledge
引用
收藏
页码:25 / 30
相关论文
共 50 条
  • [1] Deep Learning-Based Indoor Localization Using Adjacent Received Signal Strength and Domain Knowledge
    Zhang, Guangyi
    Hou, Zhanwei
    Li, Yonghui
    Vucetic, Branka
    2022 20TH MEDITERRANEAN COMMUNICATION AND COMPUTER NETWORKING CONFERENCE (MEDCOMNET), 2022,
  • [2] Deep Learning-Based Indoor Localization Using Received Signal Strength and Channel State Information
    Hsieh, Chaur-Heh
    Chen, Jen-Yang
    Nien, Bo-Hong
    IEEE ACCESS, 2019, 7 : 33256 - 33267
  • [3] Indoor Object Localization and Tracking Using Deep Learning over Received Signal Strength
    Liu, Guannan
    Wu, Hsiao-Chun
    Xiang, Weidong
    Ye, Jinwei
    Wu, Yiyan
    Pu, Limeng
    2020 IEEE INTERNATIONAL SYMPOSIUM ON BROADBAND MULTIMEDIA SYSTEMS AND BROADCASTING (BMSB), 2020,
  • [4] Unsupervised learning of indoor localization based on received signal strength
    Li, Li
    Yang, Wang
    Bhuiyan, Md Zakirul Alam
    Wang, Guojun
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2016, 16 (15): : 2225 - 2237
  • [5] Indoor Localization Using Received Signal Strength
    Obeidat, H. A.
    Abd-Alhameed, R. A.
    Noras, J. M.
    Zhu, S.
    Ghazaany, T.
    Ali, N. T.
    Elkhazmi, E.
    2013 8TH INTERNATIONAL DESIGN AND TEST SYMPOSIUM (IDT), 2013,
  • [6] A deep learning-based indoor-positioning approach using received strength signal indication and carrying mode information
    Lin, Szu-Yin
    Leu, Fang-Yie
    Ko, Chia-Yin
    Shih, Ming-Chien
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2021, 33 (23):
  • [7] Hybrid Kernel Based Machine Learning Using Received Signal Strength Measurements for Indoor Localization
    Yan, Jun
    Zhao, Lin
    Tang, Jian
    Chen, Yuwei
    Chen, Ruizhi
    Chen, Liang
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (03) : 2824 - 2829
  • [8] Rfid Indoor Localization Based Received Signal Strength
    Ahmed, Hamsa M.
    Rashid, Ahmed Noori
    2021 14TH INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ESYSTEMS ENGINEERING (DESE), 2021, : 590 - 593
  • [9] Accuracy Evaluation of Indoor Positioning by Received Signal Strength using Deep Learning
    Narita, Yuma
    Lu, Shan
    Kamabe, Hiroshi
    2022 24TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT): ARITIFLCIAL INTELLIGENCE TECHNOLOGIES TOWARD CYBERSECURITY, 2022,
  • [10] Accuracy Evaluation of Indoor Positioning by Received Signal Strength using Deep Learning
    Narita, Yuma
    Lu, Shan
    Kamabe, Hiroshi
    2021 23RD INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT 2021): ON-LINE SECURITY IN PANDEMIC ERA, 2021, : 132 - 136