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 161–170 of 206 papers

TitleStatusHype
Quantification of Ultrasonic Texture heterogeneity via Volumetric Stochastic Modeling for Tissue Characterization—0
Using Filter Banks in Convolutional Neural Networks for Texture ClassificationCode0
Combined statistical and model based texture features for improved image classification—0
Graph entropies in texture segmentation of images—0
Assessment of texture measures susceptibility to noise in conventional and contrast enhanced computed tomography lung tumour images—0
face anti-spoofing based on color texture analysisCode0
Visualizing and Understanding Deep Texture Representations—0
Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs—0
Fusing Subcategory Probabilities for Texture Classification—0
A PCA-Based Convolutional Network—0
Show:102550
← PrevPage 17 of 21Next →

No leaderboard results yet.