Texture synthesis based on sparse representation.
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Updated
Apr 25, 2018 - MATLAB
Texture synthesis based on sparse representation.
X. Wang, Y. Zhong, L. Zhang, and Y. Xu, “Spatial Group Sparsity Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 11, pp.6287-6304, 2017.
source code of my paper "Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization"
Asymmetric Semi-Nonnegative Matrix Factorization for Directed Graph Clustering
Toolbox allows to test and compare methods for Image Completion and Data Completion problems in Matlab. Presented methods use various Nonnegative Matrix Factorization and Tensor decomposition algorithms. It was based on research performed during realization of PhD.
Minimax NMF
Source code for the paper titled "Towards Weak Signal Analysis in Hyperspectral Data: A Semi-supervised Unmixing Perspective"
NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1
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