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| Home > Publications database > Automated Analysis of Remotely Sensed Images Using the Unicore Workflow Management System > print |
| 001 | 857588 | ||
| 005 | 20210129235607.0 | ||
| 020 | _ | _ | |a 978-1-5386-7150-4 |
| 024 | 7 | _ | |a 10.1109/IGARSS.2018.8519364 |2 doi |
| 024 | 7 | _ | |a 2128/20139 |2 Handle |
| 037 | _ | _ | |a FZJ-2018-06573 |
| 100 | 1 | _ | |a Memon, Mohammad Shahbaz |0 P:(DE-Juel1)132190 |b 0 |e Corresponding author |u fzj |
| 111 | 2 | _ | |a 2018 IEEE International Geoscience and Remote Sensing Symposium |g IGARSS 2018 |c Valencia |d 2018-07-22 - 2018-07-27 |w Spain |
| 245 | _ | _ | |a Automated Analysis of Remotely Sensed Images Using the Unicore Workflow Management System |
| 260 | _ | _ | |c 2018 |b IEEE |
| 300 | _ | _ | |a 1128 - 1131 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1542797823_6274 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
| 520 | _ | _ | |a The progress of remote sensing technologies leads to increased supply of high-resolution image data. However, solutions for processing large volumes of data are lagging behind: desktop computers cannot cope anymore with the requirements of macro-scale remote sensing applications; therefore, parallel methods running in High-Performance Computing (HPC) environments are essential. Managing an HPC processing pipeline is non-trivial for a scientist, especially when the computing environment is heterogeneous and the set of tasks has complex dependencies. This paper proposes an end-to-end scientific workflow approach based on the UNICORE workflow management system for automating the full chain of Support Vector Machine (SVM)-based classification of remotely sensed images. The high-level nature of UNICORE workflows allows to deal with heterogeneity of HPC computing environments and offers powerful workflow operations such as needed for parameter sweeps. As a result, the remote sensing workflow of SVM-based classification becomes re-usable across different computing environments, thus increasing usability and reducing efforts for a scientist. |
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| 536 | _ | _ | |0 G:(DE-Juel1)PHD-NO-GRANT-20170405 |x 1 |c PHD-NO-GRANT-20170405 |a PhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405) |
| 588 | _ | _ | |a Dataset connected to CrossRef Conference |
| 700 | 1 | _ | |a Cavallaro, Gabriele |0 P:(DE-Juel1)171343 |b 1 |u fzj |
| 700 | 1 | _ | |a Hagemeier, Bjorn |0 P:(DE-Juel1)132123 |b 2 |u fzj |
| 700 | 1 | _ | |a Riedel, Morris |0 P:(DE-Juel1)132239 |b 3 |u fzj |
| 700 | 1 | _ | |a Neukirchen, Helmut |0 P:(DE-HGF)0 |b 4 |
| 773 | _ | _ | |a 10.1109/IGARSS.2018.8519364 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/857588/files/igarss-2018-urc.pdf |
| 856 | 4 | _ | |y OpenAccess |x pdfa |u https://juser.fz-juelich.de/record/857588/files/igarss-2018-urc.pdf?subformat=pdfa |
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| 914 | 1 | _ | |y 2018 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
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