Despite the increasing number of successful related work-shops and panels, lifelogging has
rarely been the subject of a rigorous comparative benchmarking exercise. Following the …

The paper presents image description and classification methods which were used by
United Institute of Informatics Problems (UIIP) group for tuberculosis image classification …

Résumé ImageCLEF is the image retrieval task of the Conference and Labs of the
Evaluation Forum (CLEF). ImageCLEF has historically focused on the multimodal and …

ImageCLEF is the image retrieval task of the Conference and Labs of the Evaluation Forum
(CLEF). ImageCLEF has historically focused on the multimodal and language-independent …

Manual image annotation is a major bottleneck in the processing of medical images and the
accuracy of these reports varies depending on the clinician's expertise. Automating some or …

The Multimedia for Medicine Medico Task, running for the rst time as part of MediaEval
2017, focuses on detecting abnormalities, diseases and anatomical landmarks in images …

In this paper, we describe our methodologies in an attempt to improve the diagnosis
accuracy of drug resistant tuberculosis and also of identifying the type of tuberculosis …

Medical images are often used in clinical diagnosis. However, interpreting the insights
gained from them is often a time-consuming task even for experts. For this reason, there is a …

In this paper we present the methods and techniques performed by the IPL Group for the
concept detection task of ImageCLEF 2017. A probabilistic k-nearest neighbor approach …

In this paper, we describe our caption prediction and concept detection systems submitted
for the ImageCLEF 2017 challenge. We submitted four runs for the caption prediction task …