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» Unsupervised feature extraction using neuro-fuzzy approach
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MLDM
2005
Springer
15 years 5 months ago
Unsupervised Learning of Visual Feature Hierarchies
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
Fabien Scalzo, Justus H. Piater
WACV
2005
IEEE
15 years 5 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
ICIP
2001
IEEE
16 years 1 months ago
Image data mining from financial documents based on wavelet features
In this paper, we present a framework for clustering and classifying cheque images according to their payee-line content. The features used in the clustering and classificationpro...
Ossama El Badawy, Mahmoud R. El-Sakka, Khaled Hass...
ICIP
2006
IEEE
15 years 5 months ago
A Hierarchical Approach to Rotation-Invariant Texture Feature Extraction Based on Radon Transform Parameters
In this paper, we propose an efficient hierarchical method for extracting invariant texture features using the Gabor wavelets and Radon transform parameters. The proposed method a...
Mahmoud R. Hejazi, Yo-Sung Ho
ISDA
2009
IEEE
15 years 6 months ago
Clustering-Based Feature Selection in Semi-supervised Problems
— In this contribution a feature selection method in semi-supervised problems is proposed. This method selects variables using a feature clustering strategy, using a combination ...
Ianisse Quinzán, José Manuel Sotoca,...