230 search results - page 18 / 46 » Classification using intersection kernel support vector mach... |
JCP
2008
13 years 7 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...
CVPR
2008
IEEE
14 years 9 months ago
2008
IEEE
In this paper we demonstrate that the support vector tracking (SVT) framework first proposed by Avidan is equivalent to the canonical Lucas-Kanade (LK) algorithm with a weighted E...
JMLR
2008
13 years 7 months ago
2008
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
TRECVID
2008
13 years 9 months ago
2008
We studied a method using support vector machines (SVMs) with walk-based graph kernels for the high-level feature extraction (HLF) task. In this method, each image is first segmen...