An RSSI Indoor Localization Technique Using CNN Regression-Reference-Cited by-同舟云学术

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An RSSI Indoor Localization Technique Using CNN Regression

Published:2023-12-15 Issue: Volume: Page:80-84
ISSN:
Container-title:Proceedings of the 2023 12th International Conference on Networks, Communication and Computing
language:
Short-container-title:

Author:

Muraguchi Reiya¹^ORCID,Takano Yasuhiro¹^ORCID,Su Hsuan-Jung²^ORCID

Affiliation:

1. Dept. of Information Systems Engineering, Chitose Institute of Science and Technology, Japan

2. Graduate Institute of Communication Engineering, National Taiwan University, Taiwan and Dept. of Electrical Engineering, National Taiwan University, Taiwan

Funder

Okawa Foundation for Information and Telecommunications

National Science and Technology Council (NSTC), Taiwan

Japan Society for the Promotion of Science (JSPS)

National Taiwan University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3638837.3638849

Reference13 articles.

1. Recurrent Neural Networks for Accurate RSSI Indoor Localization

2. Issues and challenges in RSSI based target localization and tracking in wireless sensor networks

3. Performance Enhancement of an Indoor Localization System Based on Visible Light Communication Using RSSI / TDOA Hybrid Technique

4. Passive WiFi Fingerprinting Method

5. Refined characterization of RSSI with practical implications for indoor positioning

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