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ImageCLEF 2022: multimedia retrieval in medical, nature, fusion and internet applications

Conference paper

Fast facts

  • Further publishers

    Alba G. Seco de Herrera, Bogdan Ionescu, Bachelor of Science Henning Müller, Renaud Péteri, Asma Ben Abacha, Master of Science Johannes Rückert, Master of Science Louise Bloch, Master of Science Ahmad Idrissi-Yaghir, Serge Kozlovski, Yashin Dicente Cid, Vassili Kovalev, Jon Chamberlain, Adrian Clark, Antonio Campello, Hugo Schindler, Jérome Deshayes, Adrian Popescu, Liviu-Daniel Ştefan, Mihai Gabriel Constantin, Mihai Dogariu

  • Publishment

    • 2022
  • Purpose of publication

  • Organizational unit

  • Subjects

    • Computer science in general
  • Research fields

    • Life and well-being - General

Quote

A. G. Seco de Herrera, B. Ionescu, H. Müller, R. Péteri, A. Ben Abacha, C. M. Friedrich, J. Rückert, L. Bloch, R. Brüngel, A. Idrissi-Yaghir, H. Schäfer, S. Kozlovski, Y. Dicente Cid, V. Kovalev, J. Chamberlain, A. Clark, A. Campello, H. Schindler, J. Deshayes, A. Popescu, L.-D. Ştefan, M. G. Constantin, and M. Dogariu, "ImageCLEF 2022: multimedia retrieval in medical, nature, fusion and internet applications," in Advances in Information Retrieval: 44th European Conference on IR Research, 2022, pp. 382-389.

Content

ImageCLEF s 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 localization 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.

References

Notes and references

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