Learning to Locate: Adaptive Fingerprint-Based Localization With Few-Shot Relation Learning in Dynamic Indoor Environments
Author:
Affiliation:
1. Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
2. School of Electronics and Information Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, China
Funder
National Natural Science Foundation of China
Young Elite Scientist Sponsorship Program by the China Association for Science and Technology
China Post-Doctoral Science Foundation
Shenzhen Science and Technology Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications
Link
http://xplorestaging.ieee.org/ielx7/7693/10214970/10011166.pdf?arnumber=10011166
Reference51 articles.
1. TransLoc: A Heterogeneous Knowledge Transfer Framework for Fingerprint-Based Indoor Localization
2. Indoor smartphone localization via fingerprint crowdsourcing: challenges and approaches
3. Transferring localization models over time;zheng;Proc AAAI,2008
4. Adversarial Learning-Enabled Automatic WiFi Indoor Radio Map Construction and Adaptation With Mobile Robot
5. Toward Low-Overhead Fingerprint-Based Indoor Localization via Transfer Learning: Design, Implementation, and Evaluation
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