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@INPROCEEDINGS{Memon:857588,
      author       = {Memon, Mohammad Shahbaz and Cavallaro, Gabriele and
                      Hagemeier, Bjorn and Riedel, Morris and Neukirchen, Helmut},
      title        = {{A}utomated {A}nalysis of {R}emotely {S}ensed {I}mages
                      {U}sing the {U}nicore {W}orkflow {M}anagement {S}ystem},
      publisher    = {IEEE},
      reportid     = {FZJ-2018-06573},
      isbn         = {978-1-5386-7150-4},
      pages        = {1128 - 1131},
      year         = {2018},
      abstract     = {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.},
      month         = {Jul},
      date          = {2018-07-22},
      organization  = {2018 IEEE International Geoscience and
                       Remote Sensing Symposium, Valencia
                       (Spain), 22 Jul 2018 - 27 Jul 2018},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {512 - Data-Intensive Science and Federated Computing
                      (POF3-512) / PhD no Grant - Doktorand ohne besondere
                      Förderung (PHD-NO-GRANT-20170405)},
      pid          = {G:(DE-HGF)POF3-512 / G:(DE-Juel1)PHD-NO-GRANT-20170405},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      doi          = {10.1109/IGARSS.2018.8519364},
      url          = {https://juser.fz-juelich.de/record/857588},
}