Li Cheng
Wuhan University
13 Papers
35 Citations
Li Cheng is an academic researcher from Wuhan University. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 4, co-authored 13 publications.
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Papers
•Proceedings Article
Multi-Kernel Low-Rank Dictionary Pair Learning for Multiple Features Based Image Classification
Xiaoke Zhu,Xiao-Yuan Jing,Fei Wu,Di Wu,Li Cheng,Sen Li,Ruimin Hu +6 more
- 13 Feb 2017
TL;DR: This paper proposes a novel multi-kernel DL approach, named MKLDPL, which jointly learns a kernel synthesis dictionary and a kernel analysis dictionary by exploiting the class label information and imposes the low-rank regularization on the analysis dictionary.
15
Simultaneous visual-appearance-level and spatial-temporal-level dictionary learning for video-based person re-identification
TL;DR: This paper proposes a visual-appearance-level and spatial-temporal-level dictionary learning (VSDL) approach for video-based person re-id and designs a representation coefficient discriminant term for VSDL to enhance the discriminative ability of the obtained coding coefficients.
14
Structure and Performance Analysis of Signal Acquisition and Doppler Tracking in LEO Augmented GNSS Receiver.
TL;DR: In this paper, the authors proposed a novel assisted structure where GNSS signal acquisition and Doppler tracking are assisted by LEO positioning, and the coarse position with the GNSS navigation messages received from LEO, as well as the estimated clock information, is used to assist in the acquisition and tracking of GNSS.
Privacy preserving via interval covering based subclass division and manifold learning based bi-directional obfuscation for effort estimation
Fumin Qi,Xiao-Yuan Jing,Xiaoke Zhu,Fei Wu,Li Cheng +4 more
- 25 Aug 2016
TL;DR: This paper aims to provide data owners with an effective approach of privatizing their data before release by proposing a manifold learning based bi-directional data obfuscation (MLBDO) algorithm, which uses two nearest neighbors, which are selected respectively from the previous and next subclasses by utilizing the manifoldlearning based nearest neighbor selector.
7
Performance Analysis and Evaluation of Frequency-Locked Loop for Weak GNSS Signals Based on Spectral Line Interpolation
TL;DR: Three frequency estimators are introduced, which have good frequency estimation performances under low signal-to-noise ratio for GNSS weak signal tracking and propose a carrier frequency tracking method that effectively improves the accuracy of frequency estimation compared to traditional FFT estimator.