Using Received-Signal-Strength (RSS) Pre-Processing and Convolutional Neural Network (CNN) to Enhance Position Accuracy in Visible Light Positioning (VLP)

  • Li Sheng Hsu
  • , Deng Cheng Tsai
  • , Hei Man Chen
  • , Yun Han Chang
  • , Yang Liu
  • , Chi Wai Chow*
  • , Shao Hua Son
  • , Chien Hung Yeh
  • *此作品的通信作者

研究成果: Conference contribution同行評審

8 引文 斯高帕斯(Scopus)

摘要

We propose and demonstrate a received-signal-strength (RSS) pre-processing scheme to mitigate light-deficient-region occurred in visible-light-positioning (VLP) and convolutional-neural-network (CNN) to enhance VLP performance. The RSS pre-processing and CNN model are discussed.

原文English
主出版物標題2022 Optical Fiber Communications Conference and Exhibition, OFC 2022 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781557524669
出版狀態Published - 2022
事件2022 Optical Fiber Communications Conference and Exhibition, OFC 2022 - San Diego, 美國
持續時間: 6 3月 202210 3月 2022

出版系列

名字2022 Optical Fiber Communications Conference and Exhibition, OFC 2022 - Proceedings

Conference

Conference2022 Optical Fiber Communications Conference and Exhibition, OFC 2022
國家/地區美國
城市San Diego
期間6/03/2210/03/22

指紋

深入研究「Using Received-Signal-Strength (RSS) Pre-Processing and Convolutional Neural Network (CNN) to Enhance Position Accuracy in Visible Light Positioning (VLP)」主題。共同形成了獨特的指紋。

引用此