394 search results - page 3 / 79 » On Feature Extraction via Kernels |
NIPS
2008
14 years 11 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
TRECVID
2008
14 years 11 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...
ACL
2004
14 years 11 months ago
2004
We extend previous work on tree kernels to estimate the similarity between the dependency trees of sentences. Using this kernel within a Support Vector Machine, we detect and clas...
ICASSP
2009
IEEE
15 years 1 months ago
2009
IEEE
We investigate a method using support vector machines (SVMs) with walk-based graph kernels for high-level feature extraction from images. In this method, each image is first segme...
ICIP
2005
IEEE
15 years 11 months ago
2005
IEEE
Robustness and discriminability are two key issues in face recognition. In this paper, we propose a new algorithm which extracts micro-structural Gabor feature to achieve good robu...