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@ARTICLE{Tsaftaris:859907,
      author       = {Tsaftaris, Sotirios A. and Scharr, Hanno},
      title        = {{S}haring the {R}ight {D}ata {R}ight: {A} {S}ymbiosis with
                      {M}achine {L}earning},
      journal      = {Trends in plant science},
      volume       = {24},
      number       = {2},
      issn         = {1360-1385},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2019-00723},
      pages        = {P99-102},
      year         = {2019},
      abstract     = {In 2014 plant phenotyping research was not benefiting from
                      the machine learning (ML) revolution because appropriate
                      data were lacking. We report the success of the first
                      open-access data-set suitable for ML in image-based plant
                      phenotyping suitable for machine learning, fuelling a true
                      interdisciplinary symbiosis, increased awareness, and steep
                      performance improvements on key phenotyping tasks.},
      cin          = {IBG-2},
      ddc          = {570},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {583 - Innovative Synergisms (POF3-583)},
      pid          = {G:(DE-HGF)POF3-583},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:30497879},
      UT           = {WOS:000456414500001},
      doi          = {10.1016/j.tplants.2018.10.016},
      url          = {https://juser.fz-juelich.de/record/859907},
}