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ImageCLEF 2020: Multimedia retrieval in lifelogging, medical, nature, and internet applications

Ionescu, B and Müller, H and Péteri, R and Dang-Nguyen, DT and Zhou, L and Piras, L and Riegler, M and Halvorsen, P and Tran, MT and Lux, M and Gurrin, C and Chamberlain, J and Clark, A and Campello, A and Seco de Herrera, AG and Ben Abacha, A and Datla, V and Hasan, SA and Liu, J and Demner-Fushman, D and Pelka, O and Friedrich, CM and Dicente Cid, Y and Kozlovski, S and Liauchuk, V and Kovalev, V and Berari, R and Brie, P and Fichou, D and Dogariu, M and Stefan, LD and Constantin, MG (2020) ImageCLEF 2020: Multimedia retrieval in lifelogging, medical, nature, and internet applications. In: UNSPECIFIED, ? - ?.

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Abstract

© Springer Nature Switzerland AG 2020. This paper presents an overview of the 2020 ImageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum—CLEF Labs 2020 in Thessaloniki, Greece. ImageCLEF is an ongoing evaluation initiative (run since 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 will organize four main tasks: (i) a Lifelog task (videos, images and other sources) about daily activity understanding, retrieval and summarization, (ii) a Medical task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with new data and adapted tasks, (iii) a Coral task about segmenting and labeling collections of coral images for 3D modeling, and a new (iv) Web user interface task addressing the problems of detecting and recognizing hand drawn website UIs (User Interfaces) for generating automatic code. The strong participation, with over 235 research groups registering and 63 submitting over 359 runs for the tasks in 2019 shows an important interest in this benchmarking campaign. We expect the new tasks to attract at least as many researchers for 2020.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 27 Jan 2020 10:54
Last Modified: 11 May 2020 16:15
URI: http://repository.essex.ac.uk/id/eprint/26576

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