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@ARTICLE{Nguyen:1026670,
      author       = {Nguyen, Binh Duong and Steiner, Johannes and Wellmann,
                      Peter and Sandfeld, Stefan},
      title        = {{C}ombining unsupervised and supervised learning in
                      microscopy enables defect analysis of a full 4{H}-{S}i{C}
                      wafer},
      journal      = {MRS communications},
      volume       = {14},
      issn         = {2159-6859},
      address      = {Berlin},
      publisher    = {Springer},
      reportid     = {FZJ-2024-03488},
      pages        = {612-627},
      year         = {2024},
      abstract     = {Detecting and analyzing various defect types in
                      semiconductor materials is an important prerequisite for
                      understanding the underlying mechanisms and tailoring the
                      production processes. Analysis of microscopy images that
                      reveal defects typically requires image analysis tasks such
                      as segmentation and object detection. With the permanently
                      increasing amount of data from experiments, handling these
                      tasks manually becomes more and more impossible. In this
                      work, we combine various image analysis and data mining
                      techniques to create a robust and accurate, automated image
                      analysis pipeline for extracting the type and position of
                      all defects in a microscopy image of a KOH-etched 4H-SiC
                      wafer.},
      cin          = {IAS-9},
      ddc          = {670},
      cid          = {I:(DE-Juel1)IAS-9-20201008},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5111},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001233735600001},
      doi          = {10.1557/s43579-024-00563-2},
      url          = {https://juser.fz-juelich.de/record/1026670},
}