Open Access
| Issue |
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|
|
|---|---|---|
| Article Number | 02003 | |
| Number of page(s) | 7 | |
| Section | 3D Images Reconstruction and Virtual System | |
| DOI | https://doi.org/10.1051/matecconf/201823202003 | |
| Published online | 19 November 2018 | |
- D D Lee, H S Seung. Learning the parts of objects by non-negative matrix factorization. NATURE. 401(1999) [Google Scholar]
- V P Pauca, J Piper. Nonnegative matrix factorization for spectral data analysis. Linear Algebra and its Applications. 416(2006) [Google Scholar]
- L D Miao, H H Qi, Endmember Extraction From Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorization. Geoscience and Remote Sensing, 45(2007) [Google Scholar]
- A Zymnis, S J Kim, J Skaf. Hyperspectral Image Unmixing via Alternating Projected Subgradients. Asilomar Conference on Signals, Systems & Computers ASILOMAR, 13(2007) [Google Scholar]
- S Jia and Y T Qian. Constrained nonnegative matrix factorization for hyperspectral unmixing[J]. IEEE Trans. Geosci. Remote Sens., 47(2009) [Google Scholar]
- S Q Du, Y Q Shi and W L Wang. Graph regularized-based semi-supervised non-negative matrix factorization. Computer Engineering and Applications, 48(2012) [Google Scholar]
- J J Liu, Z B Wu and Z H Wei. Spatial Correlation Constrained Sparse Representation for Hyperspectral Image Classification[J]. Journal of Electronics & Information Technology. 34(2012) [Google Scholar]
- B L Chen, M Li, and J X Wang. Disease gene identification by using graph kernels and Markov random fields[J]. Science China,11(2014) [Google Scholar]
- X Y Jiang, F M Sun and H J Li. Semi-supervised Nonnegative Matrix Factorization Based on Graph Regularization and Sparseness Constraints[J]. Computer Science, 43(2016) [Google Scholar]
- P L Dobrushin. The Description of a Random Field by Means of Conditional Probabilities and Conditions of Its Regularity, Theory of Probability and its Applications, 13 (1968) [Google Scholar]
- F Spitzer. Markov Random Fields and Gibbs Ensembles, The American Mathematical Monthly, 78(1971) [Google Scholar]
- H W Deng, D A Clausi. Unsupervised image segmentation using a simple MRF model with a new implementation scheme. Pattern Recognition, 37 (2004) [Google Scholar]
- D J M Bioucas, J M P Nascimento. Hyperspectral subspace identification . Geoscience and Remote Sensing, IEEE Transactions on, 46(2008) [Google Scholar]
- B Yuan. Research on blind processing algorithms of Hyperspectral unmixing[D]. The University of Chinese Academy of Sciences (2015) [Google Scholar]
- D D Lee. Algorithms for nonnegative matrix factorization[J]. Advances in Neural Information Processing Systems, 13(2001) [Google Scholar]
- J B Wu, D-N Commutative method and its convergence[J]. Journal on Numerical Methods and Computer Applications, 23(2002) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.