Overview of ImageCLEF 2017: Information Extraction from Images

  • Bogdan Ionescu
  • Henning Müller
  • Mauricio Villegas
  • Helbert Arenas
  • Giulia Boato
  • Duc-Tien Dang-Nguyen
  • Yashin Dicente Cid
  • Carsten Eickhoff
  • Alba G. Seco de Herrera
  • Cathal Gurrin
  • Bayzidul Islam
  • Vassili Kovalev
  • Vitali Liauchuk
  • Josiane Mothe
  • Luca Piras
  • Michael Riegler
  • Immanuel Schwall
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10456)

Abstract

This paper presents an overview of the ImageCLEF 2017 evaluation campaign, an event that was organized as part of the CLEF (Conference and Labs of the Evaluation Forum) labs 2017. ImageCLEF is an ongoing initiative (started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval for providing information access to collections of images in various usage scenarios and domains. In 2017, the 15th edition of ImageCLEF, three main tasks were proposed and one pilot task: (1) a LifeLog task about searching in LifeLog data, so videos, images and other sources; (2) a caption prediction task that aims at predicting the caption of a figure from the biomedical literature based on the figure alone; (3) a tuberculosis task that aims at detecting the tuberculosis type from CT (Computed Tomography) volumes of the lung and also the drug resistance of the tuberculosis; and (4) a remote sensing pilot task that aims at predicting population density based on satellite images. The strong participation of over 150 research groups registering for the four tasks and 27 groups submitting results shows the interest in this benchmarking campaign despite the fact that all four tasks were new and had to create their own community.

Notes

Acknowledgements

This research was supported in part by the Intramural Research Program of the National Institutes of Health (NIH), National Library of Medicine (NLM), and Lister Hill National Center for Biomedical Communications (LHNCBC). It is also partly supported European Union’s Horizon 2020 Research and Innovation programme under the Grant Agreement no693210 (FabSpace 2.0).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Bogdan Ionescu
    • 1
  • Henning Müller
    • 2
  • Mauricio Villegas
    • 3
  • Helbert Arenas
    • 4
  • Giulia Boato
    • 5
  • Duc-Tien Dang-Nguyen
    • 6
  • Yashin Dicente Cid
    • 2
  • Carsten Eickhoff
    • 7
  • Alba G. Seco de Herrera
    • 8
  • Cathal Gurrin
    • 6
  • Bayzidul Islam
    • 9
  • Vassili Kovalev
    • 10
  • Vitali Liauchuk
    • 10
  • Josiane Mothe
    • 4
  • Luca Piras
    • 11
  • Michael Riegler
    • 12
  • Immanuel Schwall
    • 7
  1. 1.University Politehnica of BucharestBucharestRomania
  2. 2.University of Applied Sciences Western Switzerland (HES-SO)SierreSwitzerland
  3. 3.SearchInkBerlinGermany
  4. 4.Institut de Recherche en Informatique de ToulouseToulouseFrance
  5. 5.University of TrentoTrentoItaly
  6. 6.Dublin City UniversityDublinIreland
  7. 7.ETH ZurichZurichSwitzerland
  8. 8.National Library of MedicineBethesdaUSA
  9. 9.Technische Universität DarmstadtDarmstadtGermany
  10. 10.United Institute of Informatics ProblemsMinskBelarus
  11. 11.University of CagliariCagliariItaly
  12. 12.Simula Research LaboratoryLysakerNorway

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