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ImageCLEF 2022: Multimedia Retrieval in Medical, Nature, Fusion, and Internet Applications

Garcia Seco De Herrera, Alba and Ionescu, Bogdan and Müller, Henning and Péteri, Renaud and Ben Abacha, Asma and Friedrich, Christoph M and Rückert, Johannes and Bloch, Louise and Brüngel, Raphael and Idrissi-Yaghir, Ahmad and Schäfer, Henning and Kozlovski, Serge and Dicente Cid, Yashin and Kovalev, Vassili and Chamberlain, Jon and Clark, Adrian and Campello, Antonio and Schindler, Hugo and Deshayes, Jérôme and Popescu, Adrian and S¸tefan, Liviu-Daniel and Constantin, Mihai Gabriel and Dogariu, Mihai (2022) ImageCLEF 2022: Multimedia Retrieval in Medical, Nature, Fusion, and Internet Applications. In: 44th European Conference on Information Retrieval (ECIR), 2022-04-10 - 2022-04-14, Stavanger, Norway. (In Press)

ECIR2022_ImageCLEF.pdf - Accepted Version

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ImageCLEF is part of the Conference and Labs of the Evaluation Forum (CLEF) since 2003. CLEF 2022 will take place in Bologna, Italy. ImageCLEF is an ongoing evaluation initiative which 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 its 20th edition, ImageCLEF will have four main tasks: (i) a Medical task addressing concept annotation, caption prediction, and tuberculosis detection; (ii) a Coral task addressing the annotation and localisation of substrates in coral reef images; (iii) an Aware task addressing the prediction of real-life consequences of online photo sharing; and (iv) a new Fusion task addressing late fusion techniques based on the expertise of the pool of classifiers. In 2021, over 100 research groups registered at ImageCLEF with 42 groups submitting more than 250 runs. These numbers show that, despite the COVID-19 pandemic, there is strong interest in the evaluation campaign.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: _not provided_
Uncontrolled Keywords: User awareness; medical image classification,; medical image understanding; coral image annotation and classification; fusion; ImageCLEF benchmarking; annotated data
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 01 Mar 2022 13:53
Last Modified: 23 Sep 2022 19:52

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