ImageCLEF 2019: Multimedia Retrieval in Medicine, Lifelogging, Security and Nature

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Abstract

This paper presents an overview of the ImageCLEF 2019 lab, organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2019. ImageCLEF is an ongoing evaluation initiative (started 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 2019, the 17th edition of ImageCLEF runs four main tasks: (i) a medical task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with new data, (ii) a lifelog task (videos, images and other sources) about daily activities understanding, retrieval and summarization, (iii) a new security task addressing the problems of automatically identifying forged content and retrieve hidden information, and (iv) a new coral task about segmenting and labeling collections of coral images for 3D modeling. The strong participation, with 235 research groups registering, and 63 submitting over 359 runs, shows an important interest in this benchmark campaign.

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Ionescu, B., Müller, H., Péteri, R., Cid, Y. D., Liauchuk, V., Kovalev, V., … Campello, A. (2019). ImageCLEF 2019: Multimedia Retrieval in Medicine, Lifelogging, Security and Nature. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11696 LNCS, pp. 358–386). Springer Verlag. https://doi.org/10.1007/978-3-030-28577-7_28

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