Yuan F. Zheng

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In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of “overfitting”. Feature Selection addresses the dimensionality reduction problem by determining a subset of available features which is most essential for classification. This paper presents a novel feature selection method named(More)
A combined spatialand temporal-domain wavelet shrinkage algorithm for video denoising is presented in this paper. The spatial-domain denoising technique is a selective wavelet shrinkage method which uses a two-threshold criteria to exploit the geometry of the wavelet subbands of each video frame, and each frame of the image sequence is spatially denoised(More)
This paper presents a novel approach for navigation of cleaning robots in an unknown workspace. To do so, we propose a new map representation method as well as a complete coverage navigation method. First, we discuss a triangular cell map representation which makes the cleaning robot navigate with a shorter path and increased flexibility than a rectangular(More)
An optimal three-dimensional (3-D) coefficient tree structure for 3-D zerotree wavelet video coding is considered in this paper. The 3-D zerotree wavelet video coding is inspired by the success of the two-dimensional (2-D) zerotree wavelet image coding. Existing 3-D zerotree wavelet video codecs use the either symmetric or symmetric-alike 3-D tree(More)
A selective wavelet shrinkage algorithm for digital image denoising is presented. The performance of this method is an improvement upon other methods proposed in the literature and is algorithmically simple for large computational savings. The improved performance and computational speed of the proposed wavelet shrinkage algorithm is presented and(More)
This work addresses the description problem of a target class in the presence of negative samples or outliers. Traditional Support Vector Machines (SVM) has strong discrimination capability to distinguish the target classes but does not reject the uncharacteristic patterns well. The one-class SVM, on the other hand, provides good representation for the(More)