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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 51–75 of 206 papers

TitleStatusHype
Data-driven and Automatic Surface Texture Analysis Using Persistent Homology—0
Fractal measures of image local features: an application to texture recognition—0
VisGraphNet: a complex network interpretation of convolutional neural features—0
Inference via Sparse Coding in a Hierarchical Vision ModelCode0
Fusion of Complex Networks-based Global and Local Features for Texture Classification—0
Machine Learning Based Texture Analysis of Patella from X-Rays for Detecting Patellofemoral Osteoarthritis—0
CN-LBP: Complex Networks-based Local Binary Patterns for Texture Classification—0
A Lossless Intra Reference Block Recompression Scheme for Bandwidth Reduction in HEVC-IBC—0
Continuous monitoring of plant sub-cellular structural changes for plant and crop diseases detection by use of Intelligent Laser Speckle Classification (AI) technique—0
Unsupervised Doppler Radar-Based Activity Recognition for e-Healthcare—0
Texture-aware Video Frame Interpolation—0
Identifying the Origin of Finger Vein Samples Using Texture Descriptors—0
Smile and Laugh Expressions Detection Based on Local Minimum Key Points—0
Explainable Systematic Analysis for Synthetic Aperture Sonar Imagery—0
Riemannian information gradient methods for the parameter estimation of ECD: Some applications in image processing—0
Spatio-temporal encoding improves neuromorphic tactile texture classification—0
Enhancing Haptic Distinguishability of Surface Materials with Boosting Technique—0
TextureWGAN: Texture Preserving WGAN with MLE Regularizer for Inverse Problems—0
Dynamic texture analysis for detecting fake faces in video sequences—0
A cellular automata approach to local patterns for texture recognition—0
Learning Local Complex Features using Randomized Neural Networks for Texture Analysis—0
Self-Supervised Learning of a Biologically-Inspired Visual Texture Model—0
Harvesting, Detecting, and Characterizing Liver Lesions from Large-scale Multi-phase CT Data via Deep Dynamic Texture Learning—0
Deep Residual 3D U-Net for Joint Segmentation and Texture Classification of Nodules in Lung—0
Co-occurrence Based Texture SynthesisCode0
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