325 search results - page 28 / 65 » Statistical Properties of Kernel Principal Component Analysi... |
ICIP
2005
IEEE
14 years 10 months ago
2005
IEEE
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
JCP
2008
13 years 8 months ago
2008
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
ICMCS
2005
IEEE
14 years 2 months ago
2005
IEEE
Principal Component Analysis (PCA) has been widely used to extract features for pattern recognition problems such as object recognition. Oliva and Torralba used “spatial envelop...
IJCAI
2003
13 years 10 months ago
2003
This paper compares alternative approaches to pose estimation using visual cues from the environment. We examine approaches that derive pose estimates from global image properties...
BMCBI
2008
13 years 8 months ago
2008
Background: Bioinformatics data analysis toolbox needs general-purpose, fast and easily interpretable preprocessing tools that perform data integration during exploratory data ana...