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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 101–125 of 206 papers

TitleStatusHype
Texture Retrieval via the Scattering Transform—0
Texture Segmentation Based Video Compression Using Convolutional Neural Networks—0
Texture segmentation with Fully Convolutional Networks—0
TextureWGAN: Texture Preserving WGAN with MLE Regularizer for Inverse Problems—0
The Mehler-Fock Transform and some Applications in Texture Analysis and Color Processing—0
Unsupervised Doppler Radar-Based Activity Recognition for e-Healthcare—0
UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognition—0
VisGraphNet: a complex network interpretation of convolutional neural features—0
Visualizing and Improving Scattering Networks—0
Visualizing and Understanding Deep Texture Representations—0
Graph entropies in texture segmentation of images—0
Grey Level Co-occurrence Matrix (GLCM) Based Second Order Statistics for Image Texture Analysis—0
Harvesting, Detecting, and Characterizing Liver Lesions from Large-scale Multi-phase CT Data via Deep Dynamic Texture Learning—0
Heterogeneous patterns enhancing static and dynamic texture classification—0
Holistic Interstitial Lung Disease Detection using Deep Convolutional Neural Networks: Multi-label Learning and Unordered Pooling—0
Human activity recognition from mobile inertial sensors using recurrence plots—0
Identifying the Origin of Finger Vein Samples Using Texture Descriptors—0
Rotation Differential Invariants of Images Generated by Two Fundamental Differential Operators—0
Improved texture image classification through the use of a corrosion-inspired cellular automaton—0
Improving analytical color and texture similarity estimation methods for dataset-agnostic person reidentification—0
Improving LBP and its variants using anisotropic diffusion—0
Improving Texture Categorization with Biologically Inspired Filtering—0
Improving weather radar by fusion and classification—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
Interpretable simultaneous localization of MRI corpus callosum and classification of atypical Parkinsonian disorders using YOLOv5—0
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