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102
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TNN
2008
119views more  TNN 2008»
14 years 10 months ago
Selecting Useful Groups of Features in a Connectionist Framework
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
Debrup Chakraborty, Nikhil R. Pal
90
Voted
CJ
2004
90views more  CJ 2004»
14 years 10 months ago
Extended k-Nearest Neighbours based on Evidence Theory
An evidence theoretic classification method is proposed in this paper. In order to classify a pattern we consider its neighbours, which are taken as parts of a single source of ev...
Hui Wang, David A. Bell
94
Voted
IGARSS
2010
14 years 7 months ago
New hyperspectral data representation using binary partition tree
The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image processing tools. This paper introduces a new hierarchical ...
Silvia Valero, Philippe Salembier, Jocelyn Chanuss...
IPMI
1999
Springer
15 years 11 months ago
ANIMAL+INSECT: Improved Cortical Structure Segmentation
An algorithm for improved automatic segmentation of gross anatomical structures of the human brain is presented that merges the output of a tissue classification process with gross...
D. Louis Collins, Alex P. Zijdenbos, Wim F. C. Baa...
73
Voted
NIPS
2001
14 years 11 months ago
Covariance Kernels from Bayesian Generative Models
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Matthias Seeger