66 search results - page 4 / 14 » Learning Sparse SVM for Feature Selection on Very High Dimen... |
ECCV
2010
Springer
13 years 10 months ago
2010
Springer
Recent research has shown the effectiveness of using sparse coding(Sc) to solve many computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear sim...
ECCV
2010
Springer
13 years 11 months ago
2010
Springer
Histograms are used in almost every aspect of computer vi-4 4 sion, from visual descriptors to image representations. Histogram Inter-5 5 section Kernel (HIK) and SVM classifiers ...
CVPR
2012
IEEE
11 years 8 months ago
2012
IEEE
In this paper we examine the effect of receptive field designs on classification accuracy in the commonly adopted pipeline of image classification. While existing algorithms us...
ICCV
2011
IEEE
12 years 5 months ago
2011
IEEE
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
ICPR
2008
IEEE
14 years 6 days ago
2008
IEEE
Simple binary patterns have been successfully used for extracting feature representations for visual object classification. In this paper, we present a method to learn a set of d...