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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 26–50 of 206 papers

TitleStatusHype
Automated Identification of Tree Species by Bark Texture Classification Using Convolutional Neural Networks—0
Automated Surface Texture Analysis via Discrete Cosine Transform and Discrete Wavelet Transform—0
Automatic Segmentation and Overall Survival Prediction in Gliomas using Fully Convolutional Neural Network and Texture Analysis—0
Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs—0
Block Motion Based Dynamic Texture Analysis: A Review—0
Are Quantitative Features of Lung Nodules Reproducible at Different CT Acquisition and Reconstruction Parameters?—0
A probabilistic patch based image representation using Conditional Random Field model for image classification—0
A Gabor Filter Texture Analysis Approach for Histopathological Brain Tumor Subtype Discrimination—0
A cellular automata approach to local patterns for texture recognition—0
Classification Driven Dynamic Image Enhancement—0
Characterization of migrated seismic volumes using texture attributes: a comparative study—0
A PCA-Based Convolutional Network—0
Can autism be diagnosed with AI?—0
Classification-Driven Dynamic Image Enhancement—0
Classification with Scattering Operators—0
Clustering Images by Unmasking - A New Baseline—0
CN-LBP: Complex Networks-based Local Binary Patterns for Texture Classification—0
Color Texture Classification Based on Proposed Impulse-Noise Resistant Color Local Binary Patterns and Significant Points Selection Algorithm—0
Combined statistical and model based texture features for improved image classification—0
Completed Local Derivative Pattern for Rotation Invariant Texture Classification—0
Compositional Neural Textures—0
A non-extensive entropy feature and its application to texture classification—0
Convolutional Neural Network on Three Orthogonal Planes for Dynamic Texture Classification—0
A Theoretical Analysis of Deep Neural Networks for Texture Classification—0
Affine-Gradient Based Local Binary Pattern Descriptor for Texture Classiffication—0
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