A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images

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Bibliographic Details
Main Authors: Alberto S., Garea, Dora B., Heras, Francisco, Argüello
Format: Book
Language:English
Published: Springer 2023
Subjects:
DA
Online Access:https://link.springer.com/article/10.1007/s11227-022-04961-y
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7326
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spelling oai:localhost:PNK-73262023-03-30T03:58:23Z A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images Alberto S., Garea Dora B., Heras Francisco, Argüello DA TCANet CC BY Domain Adaptation (DA) is a technique that aims at extracting information from a labeled remote sensing image to allow classifying a different image obtained by the same sensor but at a different geographical location. This is a very complex problem from the computational point of view, specially due to the very high-resolution of multispectral images. TCANet is a deep learning neural network for DA classification problems that has been proven as very accurate for solving them. TCANet consists of several stages based on the application of convolutional filters obtained through Transfer Component Analysis (TCA) computed over the input images. 2023-03-30T03:58:23Z 2023-03-30T03:58:23Z 2023 Book https://link.springer.com/article/10.1007/s11227-022-04961-y https://dlib.phenikaa-uni.edu.vn/handle/PNK/7326 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic DA
TCANet
spellingShingle DA
TCANet
Alberto S., Garea
Dora B., Heras
Francisco, Argüello
A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images
description CC BY
format Book
author Alberto S., Garea
Dora B., Heras
Francisco, Argüello
author_facet Alberto S., Garea
Dora B., Heras
Francisco, Argüello
author_sort Alberto S., Garea
title A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images
title_short A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images
title_full A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images
title_fullStr A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images
title_full_unstemmed A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images
title_sort hybrid cuda, openmp, and mpi parallel tca-based domain adaptation for classification of very high-resolution remote sensing images
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s11227-022-04961-y
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7326
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score 8.881002