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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
A New Benchmark Dataset for Texture Image Analysis and Surface Defect Detection—0
Color Texture Classification Based on Proposed Impulse-Noise Resistant Color Local Binary Patterns and Significant Points Selection Algorithm—0
3D Geometric salient patterns analysis on 3D meshesCode0
Multiparametric Deep Learning and Radiomics for Tumor Grading and Treatment Response Assessment of Brain Cancer: Preliminary Results—0
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade—0
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
Texture image analysis and texture classification methods - A review—0
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