SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 41–50 of 206 papers

TitleStatusHype
Clustering Images by Unmasking - A New Baseline—0
CN-LBP: Complex Networks-based Local Binary Patterns for Texture Classification—0
Color Texture Classification Based on Proposed Impulse-Noise Resistant Color Local Binary Patterns and Significant Points Selection Algorithm—0
Combined statistical and model based texture features for improved image classification—0
Completed Local Derivative Pattern for Rotation Invariant Texture Classification—0
Compositional Neural Textures—0
A non-extensive entropy feature and its application to texture classification—0
Convolutional Neural Network on Three Orthogonal Planes for Dynamic Texture Classification—0
A Theoretical Analysis of Deep Neural Networks for Texture Classification—0
Affine-Gradient Based Local Binary Pattern Descriptor for Texture Classiffication—0
Show:102550
← PrevPage 5 of 21Next →

No leaderboard results yet.