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TNN
2008
119views more  TNN 2008»
13 years 4 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
PRL
1998
132views more  PRL 1998»
13 years 4 months ago
Unsupervised feature selection using a neuro-fuzzy approach
A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training. The concept of a ¯exible membersh...
Jayanta Basak, Rajat K. De, Sankar K. Pal
CVPR
1996
IEEE
13 years 8 months ago
Connectionist networks for feature indexing and object recognition
Feature indexing techniques are promising for object recognition since they can quickly reduce the set of possible matches for a set of image features. This work exploits another ...
Clark F. Olson
CVPR
2010
IEEE
13 years 12 months ago
Automatic Image Annotation Using Group Sparsity
Automatically assigning relevant text keywords to images is an important problem. Many algorithms have been proposed in the past decade and achieved good performance. Efforts have...
Shaoting Zhang, Junzhou Huang, Yuchi Huang, Yang Y...
KDD
2008
ACM
264views Data Mining» more  KDD 2008»
14 years 4 months ago
Stable feature selection via dense feature groups
Many feature selection algorithms have been proposed in the past focusing on improving classification accuracy. In this work, we point out the importance of stable feature selecti...
Lei Yu, Chris H. Q. Ding, Steven Loscalzo