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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 161–170 of 206 papers

TitleStatusHype
Riemannian information gradient methods for the parameter estimation of ECD: Some applications in image processing—0
Riesz feature representation: scale equivariant scattering network for classification tasks—0
Rigid-Motion Scattering for Texture Classification—0
Robust Adaptive Median Binary Pattern for noisy texture classification and retrieval—0
Rotational 3D Texture Classification Using Group Equivariant CNNs—0
Scale Selective Extended Local Binary Pattern for Texture Classification—0
Segmentation of Lung Tumor from CT Images using Deep Supervision—0
Segmentation of Skeletal Muscle in Thigh Dixon MRI Based on Texture Analysis—0
Self-Supervised Learning of a Biologically-Inspired Visual Texture Model—0
Sensing and Recognizing Surface Textures Using a GelSight Sensor—0
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