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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 41–50 of 206 papers

TitleStatusHype
Debiased Self-Training for Semi-Supervised LearningCode1
Encoding Spatial Distribution of Convolutional Features for Texture RepresentationCode1
Segmentation of Lung Tumor from CT Images using Deep Supervision—0
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
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