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 121–130 of 206 papers

TitleStatusHype
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade—0
Provably scale-covariant networks from oriented quasi quadrature measures in cascade—0
Psychophysical vs. learnt texture representations in novelty detection—0
Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks—0
Quantification of Ultrasonic Texture heterogeneity via Volumetric Stochastic Modeling for Tissue Characterization—0
Random Projections on Manifolds of Symmetric Positive Definite Matrices for Image Classification—0
Riemannian information gradient methods for the parameter estimation of ECD: Some applications in image processing—0
Riesz feature representation: scale equivariant scattering network for classification tasks—0
Rigid-Motion Scattering for Texture Classification—0
Robust Adaptive Median Binary Pattern for noisy texture classification and retrieval—0
Show:102550
← PrevPage 13 of 21Next →

No leaderboard results yet.