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Texture Classification

Texture Classification is a fundamental issue in computer vision and image processing, playing a significant role in many applications such as medical image analysis, remote sensing, object recognition, document analysis, environment modeling, content-based image retrieval and many more.

Source: Improving Texture Categorization with Biologically Inspired Filtering

Papers

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Showing 111–120 of 206 papers

TitleStatusHype
Fusion of complex networks and randomized neural networks for texture analysis—0
Convex Class Model on Symmetric Positive Definite Manifolds—0
Fast Rotational Sparse Coding—0
Classification-Driven Dynamic Image Enhancement—0
Wavelet Convolutional Neural NetworksCode1
Robust Adaptive Median Binary Pattern for noisy texture classification and retrieval—0
Multilayer Complex Network Descriptors for Color-Texture Characterization—0
Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks—0
A Review on Image Texture Analysis Methods—0
Innovative Texture Database Collecting Approach and Feature Extraction Method based on Combination of Gray Tone Difference Matrixes, Local Binary Patterns,and K-means Clustering—0
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