- Bogdan Ionescu17,
- Henning Müller18,
- Renaud Péteri19,
- Johannes Rückert20,
- Asma Ben Abacha21,
- Alba G. Seco de Herrera22,
- Christoph M. Friedrich20,
- Louise Bloch20,
- Raphael Brüngel20,
- Ahmad Idrissi-Yaghir20,
- Henning Schäfer20,
- Serge Kozlovski23,
- Yashin Dicente Cid24,
- Vassili Kovalev23,
- Liviu-Daniel Ştefan17,
- Mihai Gabriel Constantin17,
- Mihai Dogariu17,
- Adrian Popescu25,
- Jérôme Deshayes-Chossart25,
- Hugo Schindler25,
- Jon Chamberlain22,
- Antonio Campello26 &
- …
- Adrian Clark22
Part of the book series:Lecture Notes in Computer Science ((LNCS,volume 13390))
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Abstract
This paper presents an overview of the ImageCLEF 2022 lab that was organized as part of the Conference and Labs of the Evaluation Forum – CLEF Labs 2022. 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 2022, the 20th edition of ImageCLEF runs four main tasks: (i) amedical task that groups two previous tasks, i.e., caption analysis and tuberculosis prediction, (ii) asocial media aware task on estimating potential real-life effects of online image sharing, (iii) anature coral task about segmenting and labeling collections of coral reef images, and (iv) a newfusion task addressing the design of late fusion schemes for boosting the performance, with two real-world applications: image search diversification (retrieval) and prediction of visual interestingness (regression). The benchmark campaign received the participation of over 25 groups submitting more than 258 runs.
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Acknowledgements
The ImageCLEFaware and ImageCLEFfusion tasks were supported under the H2020 AI4Media “A European Excellence Centre for Media, Society and Democracy” project, contract\(\#951911\). The work of Louise Bloch and Raphael Brüngel was partially funded by a PhD grant from the University of Applied Sciences and Arts Dortmund (FH Dortmund), Germany. The work of Ahmad Idrissi-Yaghir and Henning Schäfer was funded by a PhD grant from the DFG Research Training Group 2535 Knowledge- and data-based personalisation of medicine at the point of care (WisPerMed).
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Politehnica University of Bucharest, Bucharest, Romania
Bogdan Ionescu, Liviu-Daniel Ştefan, Mihai Gabriel Constantin & Mihai Dogariu
University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland
Henning Müller
University of La Rochelle, La Rochelle, France
Renaud Péteri
University of Applied Sciences and Arts Dortmund, Dortmund, Germany
Johannes Rückert, Christoph M. Friedrich, Louise Bloch, Raphael Brüngel, Ahmad Idrissi-Yaghir & Henning Schäfer
Microsoft, Redmond, WA, USA
Asma Ben Abacha
University of Essex, Colchester, UK
Alba G. Seco de Herrera, Jon Chamberlain & Adrian Clark
Institute for Informatics, Minsk, Belarus
Serge Kozlovski & Vassili Kovalev
University of Warwick, Coventry, UK
Yashin Dicente Cid
Université Paris-Saclay, CEA, LIST, 91120, Palaiseau, France
Adrian Popescu, Jérôme Deshayes-Chossart & Hugo Schindler
Wellcome Trust, London, UK
Antonio Campello
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University of Bologna, Forlì, Italy
Alberto Barrón-Cedeño
University of Padua, Padova, Italy
Giovanni Da San Martino
University of Bologna, Bologna, Italy
Mirko Degli Esposti
Instituto di Scienza e Tecnologie dell' Informazione “Alessandro Faedo”, Pisa, Italy
Fabrizio Sebastiani
University of Glasgow, Glasgow, UK
Craig Macdonald
University Milano-Bicocca, Milan, Italy
Gabriella Pasi
TU Wien, Vienna, Austria
Allan Hanbury
Leipzig University, Leipzig, Germany
Martin Potthast
University of Padua, Padova, Italy
Guglielmo Faggioli
University of Padua, Padova, Italy
Nicola Ferro
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Ionescu, B.et al. (2022). Overview of the ImageCLEF 2022: Multimedia Retrieval in Medical, Social Media and Nature Applications. In: Barrón-Cedeño, A.,et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2022. Lecture Notes in Computer Science, vol 13390. Springer, Cham. https://doi.org/10.1007/978-3-031-13643-6_31
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