User data selection using CNN-feature extractor for fingerprint localization
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/11/7/11_2022XBL0037/_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] L. Xiao, A. Behboodi, and R. Mathar, “A deep learning approach to fingerprinting indoor localization solutions,” International Telecommunication Networks and Applications Conference (ITNAC), Nov. 2017. DOI: 10.1109/ATNAC.2017.8215428
3. [3] 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
4. [4] Y. Miyamoto, S. Aikawa, and S. Yamamoto, “User data selection scheme to reduce database update errors for fingerprint localization,” IEICE Commun. Express, vol. 10, no. 6, pp. 343-348, 2021. DOI: 10.1587/comex.2021XBL0051
5. [5] S. Aikawa, S. Yamamoto, and T. Muramatsu, “CNN localization using AP inverse position estimation,” 2019 IEEE Conference Antenna Measurements and Applications (CAMA2019), Oct. 23-25, 2019. DOI: 10.1109/CAMA47423.2019.8959663
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Fingerprint localization using data from different radio environments;IEICE Communications Express;2023-10
2. User data selection method using received signal strength indicator for semi-supervised learning in fingerprint localization;IEICE Communications Express;2023-03-01
3. User data selection method using received signal strength indicator for semi- supervised learning in fingerprint localization;IEICE COMMUN EXPRESS;2022
4. User data selection using CNN-feature extractor for fingerprint localization;IEICE Communications Express;2022-07-01
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3