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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 131–140 of 206 papers

TitleStatusHype
Classification Driven Dynamic Image Enhancement—0
A concatenating framework of shortcut convolutional neural networks—0
Locally-Transferred Fisher Vectors for Texture Classification—0
Visualizing and Improving Scattering Networks—0
e-Counterfeit: a mobile-server platform for document counterfeit detection—0
Wavelet Convolutional Neural Networks for Texture ClassificationCode1
Affine-Gradient Based Local Binary Pattern Descriptor for Texture Classiffication—0
A Gabor Filter Texture Analysis Approach for Histopathological Brain Tumor Subtype Discrimination—0
A Hybrid Deep Learning Approach for Texture Analysis—0
Convolutional Neural Network on Three Orthogonal Planes for Dynamic Texture Classification—0
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