Characteristic analysis of fingerprint datasets from a pragmatic view of indoor localization using machine learning approaches
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-023-05386-x.pdf
Reference77 articles.
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3. Mohammadi M, Al-Fuqaha A, Guizani M, Jun-Seok O (2017) Semisupervised deep reinforcement learning in support of IoT and smart city services. IEEE Internet Things J 5(2):624–635
4. Calderoni L, Ferrara M, Franco A, Maio D (2015) Indoor localization in a hospital environment using random forest classifiers. Expert Syst Appl 42(1):125–134
5. Van Haute T, De Poorter E, Crombez P, Lemic F, Handziski V, Wirström N, Wolisz A, Voigt T, Moerman I (2016) Performance analysis of multiple indoor positioning systems in a healthcare environment. Int J Health Geogr 15(1):1–15
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