WiCount: A Deep Learning Approach for Crowd Counting Using WiFi Signals-Reference-Cited by-同舟云学术

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WiCount: A Deep Learning Approach for Crowd Counting Using WiFi Signals

Published:2017-12 Issue: Volume: Page:
ISSN:
Container-title:2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)
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Author:

Liu Shangqing,Zhao Yanchao,Chen Bing

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8360389/8366890/08367378.pdf?arnumber=8367378

Cited by 37 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. Wireless sensing applications with Wi-Fi Channel State Information, preprocessing techniques, and detection algorithms: A survey;Computer Communications;2024-08

2. Pedestrian Flow Monitoring System for Commercial Areas Based on Deep Learning and QT;2024 International Conference on Artificial Intelligence and Digital Technology (ICAIDT);2024-06-07

3. EasyCount: Crowd Counting Based on Easy Deployment Using Commodity Wi-Fi;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

4. Wi-Diag: Robust Multisubject Abnormal Gait Diagnosis With Commodity Wi-Fi;IEEE Internet of Things Journal;2024-02-01

5. WiFi-Based Human Sensing With Deep Learning: Recent Advances, Challenges, and Opportunities;IEEE Open Journal of the Communications Society;2024

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