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» A Support Vector Clustering Method
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NLPRS
2001
Springer
15 years 8 months ago
Ensembling based on Feature Space Restructuring with Application to WSD
We propose a new ensembling method of Support Vector Machines (SVMs) based on Feature Space Restructuring. In the proposed method, the weighted majority voting method is applied f...
Hiroya Takamura, Hiroyasu Yamada, Taku Kudo, Kaoru...
ICIP
2007
IEEE
16 years 5 months ago
Motion-Based Geometry Compensation for DWT Compression of 3D mesh Sequences
In this paper, We propose an efficient compression method to encode the geometry of 3D mesh sequences of objects sharing the same connectivity. Our approach is based on the cluste...
Yasmine Boulfani-Cuisinaud, Marc Antonini
SDM
2010
SIAM
181views Data Mining» more  SDM 2010»
15 years 5 months ago
Making k-means Even Faster
The k-means algorithm is widely used for clustering, compressing, and summarizing vector data. In this paper, we propose a new acceleration for exact k-means that gives the same a...
Greg Hamerly
ICASSP
2011
IEEE
14 years 7 months ago
Wavelet footprints for detection and sorting of extracellular neural action potentials
Spike detection and sorting is a fundamental step in the analysis of extracellular neural recording. Here, we propose a combined spike detection-feature extraction algorithm that ...
Ki Yong Kwon, Karim G. Oweiss
CAIP
2007
Springer
202views Image Analysis» more  CAIP 2007»
15 years 10 months ago
Segmentation of Distinct Homogeneous Color Regions in Images
Abstract. In this paper, we present a novel algorithm to detect homogeneous color regions in images. We show its performance by applying it to skin detection. In contrast to previo...
Daniel Mohr, Gabriel Zachmann