StepNet—Deep Learning Approaches for Step Length Estimation-Reference-Cited by-同舟云学术

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StepNet—Deep Learning Approaches for Step Length Estimation

Published:2020 Issue: Volume:8 Page:85706-85713
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Klein Itzik^ORCID,Asraf Omri

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09090160.pdf?arnumber=9090160

Cited by 48 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. Deep Learning for Inertial Positioning: A Survey;IEEE Transactions on Intelligent Transportation Systems;2024-09

2. A step length estimation method based on frequency domain feature analysis and gait recognition for pedestrian dead reckoning;Sensor Review;2024-08-28

3. A Novel Distance Tracking Framework for Estimating User Position in MmWave WLANs;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

4. Context-assisted personalized pedestrian dead reckoning localization with a smartphone;Geo-spatial Information Science;2024-04-17

5. Data Fusion of Dual Foot-Mounted INS Based on Human Step Length Model;Sensors;2024-02-07

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