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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 101–110 of 206 papers

TitleStatusHype
Locally-Transferred Fisher Vectors for Texture Classification—0
Machine Learning Based Texture Analysis of Patella from X-Rays for Detecting Patellofemoral Osteoarthritis—0
Modal features for image texture classification—0
Multilayer Complex Network Descriptors for Color-Texture Characterization—0
Multilayer deep feature extraction for visual texture recognition—0
Multiparametric Deep Learning and Radiomics for Tumor Grading and Treatment Response Assessment of Brain Cancer: Preliminary Results—0
Multiscale Analysis for Improving Texture Classification—0
Multiscale Fractal Descriptors Applied to Texture Classification—0
Multi-source Transfer Learning with Convolutional Neural Networks for Lung Pattern Analysis—0
Multivariate mixture model for myocardium segmentation combining multi-source images—0
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