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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 121–130 of 206 papers

TitleStatusHype
A Review on Image Texture Analysis Methods—0
Innovative Texture Database Collecting Approach and Feature Extraction Method based on Combination of Gray Tone Difference Matrixes, Local Binary Patterns,and K-means Clustering—0
Fast and accurate computation of orthogonal moments for texture analysis—0
Texture Classification in Extreme Scale Variations using GANet—0
Texture Segmentation Based Video Compression Using Convolutional Neural Networks—0
From BoW to CNN: Two Decades of Texture Representation for Texture Classification—0
FWLBP: A Scale Invariant Descriptor for Texture ClassificationCode0
UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognition—0
Automatic Segmentation and Overall Survival Prediction in Gliomas using Fully Convolutional Neural Network and Texture Analysis—0
Human activity recognition from mobile inertial sensors using recurrence plots—0
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