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» Parsimonious Kernel Fisher Discrimination
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ICPR
2006
IEEE
14 years 8 months ago
Line Detection and Texture Characterization of Network Patterns
This paper describes a complete approach to detect, localize and describe network patterns. Such texture is automatically detected with Gaussian derivative kernels and Fisher line...
Costantino Grana, Giovanni Pellacani, Rita Cucchia...
ICMLC
2010
Springer
13 years 6 months ago
Multiple kernel learning and feature space denoising
We review a multiple kernel learning (MKL) technique called p regularised multiple kernel Fisher discriminant analysis (MK-FDA), and investigate the effect of feature space denois...
Fei Yan, Josef Kittler, Krystian Mikolajczyk
EMMCVPR
2009
Springer
14 years 2 months ago
Clustering-Based Construction of Hidden Markov Models for Generative Kernels
Generative kernels represent theoretically grounded tools able to increase the capabilities of generative classification through a discriminative setting. Fisher Kernel is the fi...
Manuele Bicego, Marco Cristani, Vittorio Murino, E...
ICPR
2006
IEEE
14 years 8 months ago
A Kernel-based Discrimination Framework for Solving Hypothesis Testing Problems with Application to Speaker Verification
Real-word applications often involve a binary hypothesis testing problem with one of the two hypotheses ill-defined and hard to be characterized precisely by a single measure. In ...
Yi-Hsiang Chao, Wei-Ho Tsai, Hsin-Min Wang, Ruei-C...
TNN
2008
182views more  TNN 2008»
13 years 7 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...