Coordinate rectification of indoor neural network localization using filters
Author:
Affiliation:
1. Graduate School of Engineering, University of Hyogo
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
General Medicine
Link
https://www.jstage.jst.go.jp/article/comex/11/8/11_2022XBL0061/_pdf
Reference7 articles.
1. [1] S. Aikawa, S. Yamamoto, and M. Morimoto, “WLAN Finger Print Localization Using Deep Learning,” IEEE APCAP Aug. 2018. DOI: 10.1109/APCAP.2018.8538306
2. [2] S. Aikawa, S. Yamamoto, and T. Muramatsu, “CNN Localization Using AP Inverse Position Estimation,” 2019 IEEE Conference Antenna Measurements and Applications(CAMA2019), OCTOBER23-25, 2019. DOI: 10.1109/CAMA47423.2019.8959663
3. [3] L. Xiao, A. Behboodi, and R. Mathar, “A Deep Learning Approach to Fingerprinting Indoor Localization Solutions,” 2017 27th International Telecommunication Networks and Applications Conference (ITNAC), 2017. DOI: 10.1109/ATNAC.2017.8215428
4. [4] A. Mittal, S. Tiku, and S. Pasricha, “Adapting Convolutional Neural Networks for Indoor Localization with Smart Mobile Devices,” GLSVLSI’18, Chicago, IL, USA, May 23-25, 2018. DOI: 10.1145/3194554.3194594
5. [5] S. Nomura, “Kalman Filter -Time Series Prediction and State Space Model Using R,” 2016, ISBN 978-4-320-11253-7
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