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Texture Classification
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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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Random Projections on Manifolds of Symmetric Positive Definite Matrices for Image Classification
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds
Improving Texture Categorization with Biologically Inspired Filtering
Texture descriptor combining fractal dimension and artificial crawlers
Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution
Online Optimization in Dynamic Environments
Sparse Coding and Dictionary Learning for Symmetric Positive Definite Matrices: A Kernel Approach
Heterogeneous patterns enhancing static and dynamic texture classification
Multiscale Fractal Descriptors Applied to Texture Classification
Supervised Texture Classification Using a Novel Compression-Based Similarity Measure
Gray Level Co-Occurrence Matrices: Generalisation and Some New Features
Classification with Scattering Operators
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