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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 191–200 of 206 papers

TitleStatusHype
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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