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 ...
[PDF] Multi-Layer Feature Fusion and Selection from Convolutional ...
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Keywords: Texture Classification, Feature Extraction, Feature Selection ... for texture feature extraction based on convolutional features fusion and selection ...
Abstract: The discrimination ability of four different methods for texture computation in ERS SAR imagery is examined and compared. Feature selection ...
The proposed approach is evaluated on three challenging datasets, and the results demonstrate the effectiveness of selecting and fusing multi-layer features for ...
Bibliographic details on Feature Selection and Fusion for Texture Classification.
This paper describes a method of unsupervised color texture segmentation by efficiently combining different features obtained from multi-channel and ...
A MCGF/MRF feature fusion algorithm for texture classification is proposed. The fused MCGF/MRF features achieved by this novel algorithm have much higher ...
ABSTRACT. This paper describes a method of unsupervised color texture segmentation by efficiently combining different features ob-.
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