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Chenshu Wu
Researcher at University of Maryland, College Park
Publications - 146
Citations - 6238
Chenshu Wu is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Computer science & Wireless. The author has an hindex of 31, co-authored 126 publications receiving 4593 citations. Previous affiliations of Chenshu Wu include University of Hong Kong & Tsinghua University.
Papers
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Proceedings ArticleDOI
Locating in fingerprint space: wireless indoor localization with little human intervention
Zheng Yang,Chenshu Wu,Yunhao Liu +2 more
TL;DR: Novel sensors integrated in modern mobile phones are investigated and leveraged to construct the radio map of a floor plan, which was previously obtained only by site survey, and LiFS, an indoor localization system based on off-the-shelf WiFi infrastructure and mobile phones is designed.
Journal ArticleDOI
WILL: Wireless Indoor Localization without Site Survey
TL;DR: This work designs WILL, an indoor localization approach based on off-the-shelf WiFi infrastructure and mobile phones and shows that WILL achieves competitive performance comparing with traditional approaches.
Journal ArticleDOI
Smartphones Based Crowdsourcing for Indoor Localization
Chenshu Wu,Zheng Yang,Yunhao Liu +2 more
TL;DR: Novel sensors integrated in modern mobile phones are investigated and leverage user motions to construct the radio map of a floor plan, which is previously obtained only by site survey, and LiFS, an indoor localization system based on off-the-shelf WiFi infrastructure and mobile phones is designed.
Journal ArticleDOI
Non-Invasive Detection of Moving and Stationary Human With WiFi
TL;DR: DeMan is a unified scheme for non-invasive detection of moving and stationary human on commodity WiFi devices that takes advantage of both amplitude and phase information of CSI to detect moving targets and considers human breathing as an intrinsic indicator of stationary human presence.
Proceedings ArticleDOI
Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi
TL;DR: Widar3.0 is the first zero-effort cross-domain gesture recognition work via Wi-Fi, a fundamental step towards ubiquitous sensing and a one-fits-all model that requires only one-time training but can adapt to different data domains.