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

Ionescu, Bogdan, Müller, Henning orcid logoORCID: 0000-0001-6800-9878, Pétri, Renaud, Dang-Nguyen, Duc-Tien orcid logoORCID: 0000-0002-2761-2213, Zhou, Liting orcid logoORCID: 0000-0002-7778-8743, Piras, Luca, Riegler, Michael, Halvorsen, Pål, Tran, Minh-Triet orcid logoORCID: 0000-0003-3046-3041, Lux, Mathias, Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968, Chamberlain, Jon, Clark, Adrian, Campello, Antonio, Seco de Herrera, Alba G., Ben Abacha, Asma, Datla, Vivek, Hasan, Sadid A., Liu, Joey, Demner-Fushman, Dina, Pelka, Obioma, Friedrich, Christoph M., Dicente Cid, Yashin, Kozlovski, Serge, Liauchuk, Vitali, Kovalev, Vassili, Berari, Raul, Brie, Paul, Fichou, Dimitri, Dogariu, Mihai, Stefan, Liviu Daniel and Constantin, Mihai Gabriel (2020) ImageCLEF 2020: multimedia retrieval in lifelogging, medical, nature, and internet applications. In: Advances in Information Retrieval, Lisbon, Portugal (Online), 14-17 Apr 2020. ISBN 978-3-030-45441-8

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)
Event Type:Conference
Uncontrolled Keywords:lifelogging retrieval and summarization; medical image classification; coral image segmentation and classification; recognition of hand drawn website UIs; ImageCLEF benchmarking; annotated data
Subjects:Computer Science > Image processing
Computer Science > Information retrieval
Computer Science > Digital video
Computer Science > Lifelog
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > INSIGHT Centre for Data Analytics
Published in: ECIR 2020: Advances in Information Retrieval. Lecture Notes in Computer Science 12036. Springer International Publishing. ISBN 978-3-030-45441-8
Publisher:Springer International Publishing
Official URL:http://dx.doi.org/10.1007/978-3-030-45442-5_69
Copyright Information:© 2020 The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:24666
Deposited On:23 Jun 2020 11:18 by Cathal Gurrin . Last Modified 20 Apr 2022 11:16

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