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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 176–200 of 206 papers

TitleStatusHype
Fractal descriptors based on the probability dimension: a texture analysis and classification approach—0
Gabor wavelets combined with volumetric fractal dimension applied to texture analysis—0
Texture analysis using volume-radius fractal dimension—0
Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices—0
Amoeba Techniques for Shape and Texture Analysis—0
Neighborhood Rank Order Coding for Robust Texture Analysis and Feature Extraction—0
Performance evaluation of wavelet scattering network in image texture classification in various color spaces—0
Adaptive texture energy measure method—0
Persistence-based Structural Recognition—0
Lacunarity Analysis on Image Patterns for Texture Classification—0
Improving weather radar by fusion and classification—0
Texture Based Image Segmentation of Chili Pepper X-Ray Images Using Gabor Filter—0
PCANet: A Simple Deep Learning Baseline for Image Classification?Code0
Block Motion Based Dynamic Texture Analysis: A Review—0
Rigid-Motion Scattering for Texture Classification—0
Random Projections on Manifolds of Symmetric Positive Definite Matrices for Image Classification—0
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds—0
Improving Texture Categorization with Biologically Inspired Filtering—0
Texture descriptor combining fractal dimension and artificial crawlers—0
Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution—0
Online Optimization in Dynamic Environments—0
Sensing and Recognizing Surface Textures Using a GelSight Sensor—0
Enriching Texture Analysis with Semantic Data—0
Heterogeneous patterns enhancing static and dynamic texture classification—0
Sparse Coding and Dictionary Learning for Symmetric Positive Definite Matrices: A Kernel ApproachCode0
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