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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
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
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