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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

Showing 191200 of 206 papers

TitleStatusHype
FWLBP: A Scale Invariant Descriptor for Texture ClassificationCode0
Learning rotation invariant convolutional filters for texture classificationCode0
face anti-spoofing based on color texture analysisCode0
Spatio-spectral networks for color-texture analysisCode0
Quantitative Measures for Passive Sonar Texture AnalysisCode0
Enhanced Wavelet Scattering Network for image inpainting detectionCode0
Local Rotation Invariance in 3D CNNsCode0
PCANet: A Simple Deep Learning Baseline for Image Classification?Code0
Self-Supervised Learning to Guide Scientifically Relevant Categorization of Martian Terrain ImagesCode0
VORTEX: Challenging CNNs at Texture Recognition by using Vision Transformers with Orderless and Randomized Token EncodingsCode0
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