( en | de | ru )

 

Disambiguation of "Bioucas-Dias, José M."

Author of the publication

copydeleteadd this publication to your clipboard
Fast hyperspectral unmixing in presence of sparse multiple scattering nonlinearities.

, , , , and . ICASSP, page 3111-3115. IEEE, (2017)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Humberto Jorge José

Nadine José Gonzalez

Manjula Dias-Hargarter

Marcelo Dias

José Navarrete

 

Other publications of authors with the same name

Parallel implementation of vertex component analysis for hyperspectral endmember extraction., , , , and . IGARSS, page 4078-4081. IEEE, (2012)Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse Representations., and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 11 (3): 730-742 (2018)Linear Spectral Unmixing via Matrix Factorization: Identifiability Criteria for Sparse Abundances., and . IGARSS, page 6155-6158. IEEE, (2018)Total Variation-Based Image Deconvolution: a Majorization-Minimization Approach., , and . ICASSP (2), page 861-864. IEEE, (2006)A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing., , , , , , , and . IEEE Signal Process. Mag., 31 (1): 67-81 (2014)Hyperspectral unmixing algorithm via dependent component analysis., and . IGARSS, page 4033-4036. IEEE, (2007)Learning dependent sources using mixtures of Dirichlet: Applications on hyperspectral unmixing., and . WHISPERS, page 1-5. IEEE, (2009)Semisupervised Self-Learning for Hyperspectral Image Classification., , , , , and . IEEE Trans. Geosci. Remote. Sens., 51 (7-1): 4032-4044 (2013)Generalized Composite Kernel Framework for Hyperspectral Image Classification., , , , and . IEEE Trans. Geosci. Remote. Sens., 51 (9): 4816-4829 (2013)Effect of Denoising in Band Selection for Regression Tasks in Hyperspectral Datasets., , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 6 (2-2): 473-481 (2013)