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—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)
—A combined spatial-and 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)
— Support Vector Machines (SVM) is originally designed for binary classification. The conventional way to extend it to multi-class scenario is to decompose an M-class problem into a series of two-class problems, for which one-against-all is the earliest and one of the most widely used implementations. One drawback of this method, however, is that when the(More)
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(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)