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dc.contributor.authorIonescu, Bogdan
dc.contributor.authorMüller, Henning
dc.contributor.authorPéteri, Renaud
dc.contributor.authorAbacha, Asma Ben
dc.contributor.authorDatla, Vivek
dc.contributor.authorHasan, Sadid A.
dc.contributor.authorDemner-Fushman, Dina
dc.contributor.authorKozlovski, Serge
dc.contributor.authorLiauchuk, Vitali
dc.contributor.authorCid, Yashin Dicente
dc.contributor.authorKovalev, Vassili
dc.contributor.authorPelka, Obioma
dc.contributor.authorFriedrich, Christoph M.
dc.contributor.authorGarcía Seco de Herrera, Alba
dc.contributor.authorNinh, Van-Tu
dc.contributor.authorLe, Tu-Khiem
dc.contributor.authorZhou, Liting
dc.contributor.authorPiras, Luca
dc.contributor.authorRiegler, Michael
dc.contributor.authorHalvorsen, Pål
dc.contributor.authorTran, Minh-Triet
dc.contributor.authorLux, Mathias
dc.contributor.authorGurrin, Cathal
dc.contributor.authorDang Nguyen, Duc Tien
dc.contributor.authorChamberlain, Jon
dc.contributor.authorClark, Adrian
dc.contributor.authorCampello, Antonio
dc.contributor.authorFichou, Dimitri
dc.contributor.authorBerari, Raul
dc.contributor.authorBrie, Paul
dc.contributor.authorDogariu, Mihai
dc.contributor.authorŞtefan, Liviu Daniel
dc.contributor.authorConstantin, Mihai Gabriel
dc.date.accessioned2021-06-02T08:35:25Z
dc.date.available2021-06-02T08:35:25Z
dc.date.created2020-10-19T12:00:46Z
dc.date.issued2020
dc.PublishedLecture Notes in Computer Science (LNCS). 2020, 12260 311-341.
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/11250/2757320
dc.description.abstractThis paper presents an overview of the ImageCLEF 2020 lab that was organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2020. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2020, the 18th edition of ImageCLEF runs four main tasks: (i) a medical task that groups three previous tasks, i.e., caption analysis, tuberculosis prediction, and medical visual question answering and question generation, (ii) a lifelog task (videos, images and other sources) about daily activity understanding, retrieval and summarization, (iii) a coral task about segmenting and labeling collections of coral reef images, and (iv) a new Internet task addressing the problems of identifying hand-drawn user interface components. Despite the current pandemic situation, the benchmark campaign received a strong participation with over 40 groups submitting more than 295 runs.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.titleOverview of the ImageCLEF 2020: Multimedia Retrieval in Medical, Lifelogging, Nature, and Internet Applicationsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holderCopyright Springer Nature Switzerland AG 2020en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1
dc.identifier.doi10.1007/978-3-030-58219-7_22
dc.identifier.cristin1840491
dc.source.journalLecture Notes in Computer Science (LNCS)en_US
dc.source.4012260
dc.source.pagenumber311-341en_US
dc.identifier.citationLecture Notes in Computer Science (LNCS). 2020, 12260, 311-341en_US
dc.source.volume12260en_US


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