Machine Learning-based Localization
Machine Learning-Based Localization is a machine learning-driven approach to estimating the physical position of Internet of Things (IoT) devices by leveraging data-driven models to infer location from sensor or signal measurements, distinguished from conventional geometric or probabilistic methods by its reliance on learned patterns from training data.
506
Publications
21.2K
Citations
1.7K
Authors
600
Institutions
Publications per year
2017–2026
393
Parents
506
A Survey of Machine Learning for Indoor Positioning
Ahasanun Nessa, Bhagawat Adhikari, Fatima Hussain et al. · IEEE Access · 2020 · 258 citations · Full text
1–5 of 506
1.7K
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Hong Kong University of Science and Technology, Hong Kong SAR China
7 publications · 576 citations
7
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6
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1–5 of 1.7K
600
Nanyang Technological University
Singapore, Singapore
14 h-index
35 publications
2.2K citations

University of Science and Technology Beijing
Beijing, China
10 h-index
21 publications
747 citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
9 h-index
22 publications
804 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
7 h-index
21 publications
1.7K citations
Wuhan University
Wuhan, China
7 h-index
20 publications
1.5K citations
Seoul National University
Seoul, South Korea
7 h-index
19 publications
763 citations

Chinese Academy of Sciences
Beijing, China
7 h-index
14 publications
370 citations
Nanjing University of Posts and Telecommunications
Nanjing, China
7 h-index
22 publications
660 citations
1–8 of 600
27 publications · 2K citations
24
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27 publications · 1.2K citations
19
h-index
18 publications · 687 citations
17
h-index
13 publications · 523 citations
12
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9 publications · 437 citations
10
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