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NPL
2002
145views more  NPL 2002»
13 years 11 months ago
Hybrid Feedforward Neural Networks for Solving Classification Problems
A novel multistage feedforward network is proposed for efficient solving of difficult classification tasks. The standard Radial Basis Functions (RBF) architecture is modified in or...
Iulian B. Ciocoiu
NECO
1998
151views more  NECO 1998»
13 years 11 months ago
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can e ciently compute principal comp...
Bernhard Schölkopf, Alex J. Smola, Klaus-Robe...
PR
2000
129views more  PR 2000»
13 years 11 months ago
Personal identification based on handwriting
In this paper, a novel algorithm is presented for writer identification from handwritings. Principal Component Analysis is applied to the gray-scale handwriting images to find a s...
H. E. S. Said, T. N. Tan, Keith D. Baker
PAMI
2000
95views more  PAMI 2000»
13 years 11 months ago
Boundary Finding with Prior Shape and Smoothness Models
Yongmei Wang, Lawrence H. Staib
CCE
2005
13 years 11 months ago
On-line monitoring of a sugar crystallization process
The present paper reports a comparative evaluation of four multivariate statistical process control (SPC) techniques for the on-line monitoring of an industrial sugar crystallizat...
A. Simoglou, Petia Georgieva, E. B. Martin, A. J. ...
TNN
2008
141views more  TNN 2008»
13 years 11 months ago
MPCA: Multilinear Principal Component Analysis of Tensor Objects
This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern rec...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
PAMI
2008
200views more  PAMI 2008»
13 years 11 months ago
Principal Component Analysis Based on L1-Norm Maximization
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...
Nojun Kwak
PAMI
2008
153views more  PAMI 2008»
13 years 11 months ago
Correlation Metric for Generalized Feature Extraction
Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms using ...
Yun Fu, Shuicheng Yan, Thomas S. Huang
ENGL
2007
180views more  ENGL 2007»
13 years 11 months ago
Biological Data Mining for Genomic Clustering Using Unsupervised Neural Learning
— The paper aims at designing a scheme for automatic identification of a species from its genome sequence. A set of 64 three-tuple keywords is first generated using the four type...
Shreyas Sen, Seetharam Narasimhan, Amit Konar
CAGD
2007
119views more  CAGD 2007»
13 years 11 months ago
Principal curvatures from the integral invariant viewpoint
The extraction of curvature information for surfaces is a basic problem of Geometry Processing. Recently an integral invariant solution of this problem was presented, which is bas...
Helmut Pottmann, Johannes Wallner, Yong-Liang Yang...