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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 91–100 of 206 papers

TitleStatusHype
Clustering Images by Unmasking - A New Baseline—0
Psychophysical vs. learnt texture representations in novelty detection—0
Persistence Curves: A canonical framework for summarizing persistence diagramsCode0
Shortest Paths in HSI Space for Color Texture Classification—0
Deep CNNs Meet Global Covariance Pooling: Better Representation and GeneralizationCode1
Texture image analysis and texture classification methods - A review—0
Boundary-Preserved Deep Denoising of the Stochastic Resonance Enhanced Multiphoton Images—0
Segmentation of Skeletal Muscle in Thigh Dixon MRI Based on Texture Analysis—0
Provably scale-covariant networks from oriented quasi quadrature measures in cascade—0
Bone Texture Analysis for Prediction of Incident Radio-graphic Hip Osteoarthritis Using Machine Learning: Data from the Cohort Hip and Cohort Knee (CHECK) study—0
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