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GPU-CUDA

Implementation of Abundance Estimation Algorithms Using NVIDIA CUDA. About the initialization of the algorithm…. In: Dr. Yahya Masalmah's Thesis. The unmixing of the hyperspectral imagery (HI) cube obtained from the images (of a certain area) formed by the spectral bands taken by the sensors. Is not done in the original HI because of its high quantity of data. In [1] the solution presented to reduce the data of HI (without losing much of the original spectral information) is band selection. 5 Compute X 1.

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GPU-CUDA | gpucuda.ece.uprm.edu Reviews
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Implementation of Abundance Estimation Algorithms Using NVIDIA CUDA. About the initialization of the algorithm…. In: Dr. Yahya Masalmah's Thesis. The unmixing of the hyperspectral imagery (HI) cube obtained from the images (of a certain area) formed by the spectral bands taken by the sensors. Is not done in the original HI because of its high quantity of data. In [1] the solution presented to reduce the data of HI (without losing much of the original spectral information) is band selection. 5 Compute X 1.
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1 gpu cuda
2 goal
3 author christine
4 0 comments
5 author christian
6 in uncategorized
7 further thesis reading
8 image from
9 multiplicative updating rules
10 in the paper
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gpu cuda,goal,author christine,0 comments,author christian,in uncategorized,further thesis reading,image from,multiplicative updating rules,in the paper,problem given by,theorem 1,the euclidean distance,v â wh,theorem 2,the divergence,in cuda,code,pages 9
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GPU-CUDA | gpucuda.ece.uprm.edu Reviews

https://gpucuda.ece.uprm.edu

Implementation of Abundance Estimation Algorithms Using NVIDIA CUDA. About the initialization of the algorithm…. In: Dr. Yahya Masalmah's Thesis. The unmixing of the hyperspectral imagery (HI) cube obtained from the images (of a certain area) formed by the spectral bands taken by the sensors. Is not done in the original HI because of its high quantity of data. In [1] the solution presented to reduce the data of HI (without losing much of the original spectral information) is band selection. 5 Compute X 1.

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GPU-CUDA

Implementation of Abundance Estimation Algorithms Using NVIDIA CUDA. About the initialization of the algorithm…. In: Dr. Yahya Masalmah's Thesis. The unmixing of the hyperspectral imagery (HI) cube obtained from the images (of a certain area) formed by the spectral bands taken by the sensors. Is not done in the original HI because of its high quantity of data. In [1] the solution presented to reduce the data of HI (without losing much of the original spectral information) is band selection. 5 Compute X 1.

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