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In this paper, a novel texture classification method using selected and combined features from wavelet frame and steerable pyramid decompositions has been ...
In this paper, a novel texture classification method using selected and combined features from wavelet frame and steerable pyramid decompositions has been ...
LNCS 3497 - Feature Selection and Fusion for Texture Classification
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Abstract. In this paper, a novel texture classification method using selected and combined features from wavelet frame and steerable pyramid decompositions.
A novel texture classification method using selected and combined features from wavelet frame and steerable pyramid decompositions has been proposed and can ...
In this paper, we propose methods where Convolution Neural Network (CNN) features are used for feature extraction and Support Vector machine is used as ...
Missing: Selection | Show results with:Selection
Texture fusion and feature selection ... By combining features derived from different texture models, the classification accuracy increased significantly.
The extracted and selected features from multiple layers can be further manageable by a classifier. The proposed approach is evaluated on three challenging ...
This paper presents an evaluation of a number of feature selection techniques for classification in a biomedical image texture dataset (2-DE gel images), with ...
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Bibliographic details on Feature Selection and Fusion for Texture Classification.