1. [1] D. Taniuchi and T. Maekawa, “Robust indoor positioning method based on automatic update of Wi-Fi fingerprints,” Transactions of the Information Processing Society of Japan, vol. 55, no. 1, pp. 280-288, Jan. 2014.
2. [2] D. Taniuchi and T. Maekawa, “Robust Wi-Fi fingerprinting based on boosting considering signal strength stability of APs,” IPSJ SIG Technical Report, vol. 2014-UBI-43, no. 3, July 2014.
3. [3] K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” arXiv: 1512.03385v1 [cs.CV], Dec. 2015.
4. [4] R.S. Sinha and S.-H. Hwang, “Comparison of CNN applications for RSSI-based fingerprint indoor localization,” MDPI Electronics 2019, vol. 8, p. 989, 2019. DOI: 10.3390/electronics8090989
5. [5] Y. Sakanishi, S. Aikawa, S. Yamamoto, and Y. Sakai, “An experimental study on improving accuracy of location estimation in finger print using CNN and ResNet,” IEICE ICTTC2021, Dec. 2021.