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» Dominant Sets and Hierarchical Clustering
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KAIS
2006
110views more  KAIS 2006»
13 years 7 months ago
Multi-step density-based clustering
Abstract. Data mining in large databases of complex objects from scientific, engineering or multimedia applications is getting more and more important. In many areas, complex dista...
Stefan Brecheisen, Hans-Peter Kriegel, Martin Pfei...
AAAI
2011
12 years 7 months ago
Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection
Semi-supervised support vector machines (S3VMs) are a kind of popular approaches which try to improve learning performance by exploiting unlabeled data. Though S3VMs have been fou...
Yu-Feng Li, Zhi-Hua Zhou
CORR
2011
Springer
151views Education» more  CORR 2011»
13 years 2 months ago
A supervised clustering approach for fMRI-based inference of brain states
We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject’s behavior during a scanning se...
Vincent Michel, Alexandre Gramfort, Gaël Varo...
ICIP
2003
IEEE
14 years 9 months ago
Quadruped gait analysis using sparse motion information
In this paper we propose a system that recognises gait and quadruped structure from a sparse set of tracked points. In this work the motion information is derived from dynamic wil...
David P. Gibson, Neill W. Campbell, Barry T. Thoma...
3DPVT
2004
IEEE
107views Visualization» more  3DPVT 2004»
13 years 11 months ago
An Easy Viewer for Out-of-Core Visualization of Huge Point-Sampled Models
In this paper, we propose a viewer for huge point-sampled models by combining out-of-core technologies with view-dependent level-of-detail (LOD) control. This viewer is designed o...
Fang Meng, Hongbin Zha