Overview of ImageCLEF 2018 :
challenges, datasets and evaluation
Ionescu Bogdan, Müller Henning, Villegas Mauricio, García Seco de Herrera Alba, Eickhoff Carsten, Andrearczyk Vincent, Dicente Cid Yashin, Liauchuk Vitali, Kovalev Vassili, Hasan Sadid A., Ling Yuan, Farri Oladimeji, Liu Joey, Lungren Matthew, Dang-Nguyen Duc-Tien, Piras Luca, Riegler Michael, Zhou Liting, Lux Mathias, Gurrin Cathal
, Experimental IR meets multilinguality, multimodality, and interaction : 9th International Conference of the CLEF Association, CLEF 2018, Avignon, France, September 10-14, 2018, Proceedings (Pp. 309-334). 2018, Cham : Springer
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Abstract. This paper presents an overview of the ImageCLEF 2018 evaluation campaign, an event that was organized as part of the CLEF (Conference and Labs of the Evaluation Forum) Labs 2018. ImageCLEF is an ongoing initiative (it started in 2003) that promotes the evalua-tion of technologies for annotation, indexing and retrieval with the aim of providing information access to collections of images in various us-age scenarios and domains. In 2018, the 16th edition of ImageCLEF ran three main tasks and a pilot task: 1) a caption prediction task that aims at predicting the caption of a figure from the biomedical literature based only on the figure image; 2) a tuberculosis task that aims at detecting the tuberculosis type, severity and drug resistance from CT (Computed Tomography) volumes of the lung; 3) a LifeLog task (videos, images and other sources) about daily activities understanding and moment re-trieval, and 4) a pilot task on visual question answering where systems are tasked with answering medical questions. The strong participation, with over 100 research groups registering and 31 submitting results for the tasks, shows an increasing interest in this benchmarking campaign.