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Kwok-Wai Cheung

Researcher at University of Hong Kong

Publications -  66
Citations -  2244

Kwok-Wai Cheung is an academic researcher from University of Hong Kong. The author has contributed to research in topics: Wavelet transform & Motion estimation. The author has an hindex of 18, co-authored 64 publications receiving 1962 citations. Previous affiliations of Kwok-Wai Cheung include Chu Hai College of Higher Education & Hong Kong Applied Science and Technology Research Institute.

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Journal ArticleDOI

Least squares algorithms for time-of-arrival-based mobile location

TL;DR: It is shown that the CWLS estimator yields better performance than the LS method and achieves both the Crame/spl acute/r-Rao lower bound and the optimal circular error probability at sufficiently high signal-to-noise ratio conditions.
Journal ArticleDOI

A constrained least squares approach to mobile positioning: algorithms and optimality

TL;DR: This paper presents a constrained weighted least squares (CWLS) mobile positioning approach that encompasses all the above described measurement cases and shows that all the developed CWLS location estimators achieve zero bias and the Cramér-Rao lower bound approximately when measurement error variances are small.
Journal ArticleDOI

Integration of image quality and motion cues for face anti-spoofing

TL;DR: An extendable multi-cues integration framework for face anti-spoofing using a hierarchical neural network is proposed, which can fuse image quality cues and motion cues for liveness detection.
Journal ArticleDOI

A multidimensional scaling framework for mobile location using time-of-arrival measurements

TL;DR: A simple algorithm is devised using time-of-arrival measurements of the signal from the mobile station received at three or more base stations, via modifying the classical multidimensional scaling technique, which has been developed for analyzing data obtained from physical, biological, and behavioral science.
Proceedings ArticleDOI

Accurate approximation algorithm for TOA-based maximum likelihood mobile location using semidefinite programming

TL;DR: Simulation results indicate that this semidefinite relaxation location estimator provides mean square position error performance close to the Cramer-Rao lower bound for a wide range of TOA measurement error levels.