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Liqing Zhang

Researcher at Shanghai Jiao Tong University

Publications -  337
Citations -  10883

Liqing Zhang is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Computer science & Feature extraction. The author has an hindex of 37, co-authored 297 publications receiving 8886 citations. Previous affiliations of Liqing Zhang include South China University of Technology & National University of Singapore.

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Journal ArticleDOI

Noninvasive BCIs: Multiway Signal-Processing Array Decompositions

TL;DR: The brain-computer interface neuroscience paradigm allows researchers to develop a new class of bioengineering control devices and robots, offering promise for rehabilitation and other medical applications as well as exploring possibilities for advanced human-computer interfaces.
Proceedings ArticleDOI

MindFinder: interactive sketch-based image search on millions of images

TL;DR: By scaling up the database to more than two million images, MindFinder not only helps users to easily present whatever they are imagining, but also has the potential to retrieve the most desired images in their mind.
Journal ArticleDOI

Feature learning from incomplete EEG with denoising autoencoder

TL;DR: In this article, the authors employed the Lomb-Scargle periodogram to estimate the spectral power from incomplete EEG, and Denoising Autoencoder (DAE) for learning.
Journal ArticleDOI

Higher Order Partial Least Squares (HOPLS): A Generalized Multilinear Regression Method

TL;DR: A systematic comparison on both synthetic data and real-world decoding of 3D movement trajectories from electrocorticogram signals demonstrate the advantages of HOPLS over the existing methods in terms of better predictive ability, suitability to handle small sample sizes, and robustness to noise.
Proceedings ArticleDOI

Determining the radiometric response function from a single grayscale image

TL;DR: With this single-image method, radiometric calibration becomes possible to perform in many instances where the camera is unknown, and a prior model of radiometric response functions is employed to deal with incomplete data.