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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 151–175 of 206 papers

TitleStatusHype
Texture Based Image Segmentation of Chili Pepper X-Ray Images Using Gabor Filter—0
Adaptive Segmentation of Knee Radiographs for Selecting the Optimal ROI in Texture Analysis—0
Texture Classification in Extreme Scale Variations using GANet—0
Texture Classification Network Integrating Adaptive Wavelet Transform—0
Texture Classification of MR Images of the Brain in ALS using CoHOG—0
Texture Classification using Block Intensity and Gradient Difference (BIGD) Descriptor—0
Texture descriptor combining fractal dimension and artificial crawlers—0
Texture Discrimination via Hilbert Curve Path Based Information Quantifiers—0
Texture features in medical image analysis: a survey—0
Texture image analysis and texture classification methods - A review—0
Texture image analysis based on joint of multi directions GLCM and local ternary patterns—0
Texture Representation via Analysis and Synthesis with Generative Adversarial Networks—0
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
Texture Characterization by Using Shape Co-occurrence Patterns—0
2-d signature of images and texture classification—0
A cellular automata approach to local patterns for texture recognition—0
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