no code implementations • 26 Dec 2021 • Hamidreza Mousavi, Maryam Imani, Hassan Ghassemian
Following the great success of curriculum learning in the area of machine learning, a novel deep curriculum learning method proposed in this paper, entitled DCL, particularly for the classification of fully polarimetric synthetic aperture radar (PolSAR) data.
no code implementations • 4 Jun 2015 • Roozbeh Rajabi, Hassan Ghassemian
Sparseness constraint on both spectral signatures and abundance fractions matrices are used in this paper.
no code implementations • 3 Nov 2014 • Roozbeh Rajabi, Hassan Ghassemian
The presence percentages of endmembers in mixed pixels are called abundance fractions.
1 code implementation • 12 Aug 2014 • Roozbeh Rajabi, Hassan Ghassemian
In this letter we proposed using multilayer NMF (MLNMF) for the purpose of hyperspectral unmixing.
no code implementations • 22 Oct 2013 • Roozbeh Rajabi, Hassan Ghassemian
On the other hand panchromatic image has a better spatial resolution.
no code implementations • 29 Jun 2013 • Roozbeh Rajabi, Hassan Ghassemian
In this paper we have used graph regularized (GNMF) method with sparseness constraint to unmix hyperspectral data.