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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 71–80 of 206 papers

TitleStatusHype
3D Solid Spherical Bispectrum CNNs for Biomedical Texture AnalysisCode0
Spectral Data Augmentation Techniques to quantify Lung Pathology from CT-images—0
Deep Transfer Learning for Texture Classification in Colorectal Cancer Histology—0
Introducing Anisotropic Minkowski Functionals for Local Structure Analysis and Prediction of Biomechanical Strength of Proximal Femur Specimens—0
Local Rotation Invariance in 3D CNNsCode0
Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset—0
Texture Classification using Block Intensity and Gradient Difference (BIGD) Descriptor—0
Histogram Layers for Texture AnalysisCode1
Deep Learning Algorithms for Coronary Artery Plaque Characterisation from CCTA Scans—0
Rotation Differential Invariants of Images Generated by Two Fundamental Differential Operators—0
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