ICDAR
2011
IEEE
12 years 4 months ago
2011
IEEE
– Better understanding the document logical components is crucial to many applications, e.g., document classification or data integration. As the development of digital libraries...
TCBB
2010
12 years 11 months ago
2010
Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that e...
PAA
2010
12 years 11 months ago
2010
Abstract Fingerprint classification represents an important preprocessing step in fingerprint identification, which can be very helpful in reducing the cost of searching large fing...
BMVC
2010
13 years 2 months ago
2010
This paper shows how semantic attribute features can be used to improve object classification performance. The semantic attributes used fall into five groups: scene (e.g. `road�...
SMC
2010
IEEE
13 years 2 months ago
2010
IEEE
—Text classification is a widely studied topic in the area of machine learning. A number of techniques have been developed to represent and classify text documents. Most of the t...
PAMI
2002
13 years 4 months ago
2002
Discriminants are often used in pattern recognition to separate clusters of points in some multidimensional "feature" space. This paper provides two fast and simple techn...
TKDE
2008
13 years 4 months ago
2008
The linear discriminant analysis (LDA) technique is very popular in pattern recognition for dimensionality reduction. It is a supervised learning technique that finds a linear tran...
BIOINFORMATICS
2005
13 years 4 months ago
2005
A key issue in supervised protein classification is the representation of input sequences of amino acids. Recent work using string kernels for protein data has achieved state-of-t...
PRL
2006
13 years 4 months ago
2006
In earlier papers, it was shown that recognizing persons using their brain patterns evoked during visual stimulus is possible. In this paper, several modifications are proposed to...
PRL
2008
13 years 4 months ago
2008
: Matrix-pattern-oriented Least Squares Support Vector Classifier (MatLSSVC) can directly classify matrix patterns and has a superior classification performance than its vector ver...