ImageCLEF 2023 Highlight: Multimedia Retrieval in Medical, Social Media and Content Recommendation Applications
Abstract
In this paper, we provide an overview of the upcoming ImageCLEF campaign. ImageCLEF is part of the CLEF Conference and Labs of the Evaluation Forum since 2003. ImageCLEF, the Multimedia Retrieval task in CLEF, is an ongoing evaluation initiative that promotes the evaluation of technologies for annotation, indexing, and retrieval of multimodal data with the aim of providing information access to large collections of data in various usage scenarios and domains. In its 21st edition, ImageCLEF 2023 will have four main tasks: (i) a Medical task addressing automatic image captioning, synthetic medical images created with GANs, Visual Question Answering for colonoscopy images, and medical dialogue summarization; (ii) an Aware task addressing the prediction of real-life consequences of online photo sharing; (iii) a Fusion task addressing late fusion techniques based on the expertise of a pool of classifiers; and (iv) a Recommending task addressing cultural heritage content-recommendation. In 2022, ImageCLEF received the participation of over 25 groups submitting more than 258 runs. These numbers show the impact of the campaign. With the COVID-19 pandemic now over, we expect that the interest in participating, especially at the physical CLEF sessions, will increase significantly in 2023.
Ahmad Idrissi-Yaghir
Researcher in the first cohort
My research interests include Deep Learning, Natural Language Processing, and Information Retrieval.
Christoph M. Friedrich
Principal Investigator
My research interests include Deep Learning, Computer Vision, Radiomics, and Explainable AI.
Henning Schäfer
Researcher in the first cohort
My research interests include Deep Learning, Computer Vision, Radiomics, and Explainable AI.
Louise Bloch
Associated Researcher
My research interests include interpretable machine learning, mutlimodal deep learning, and medical image processing.
Raphael Brüngel
Associated Researcher
My research interests include artificial intelligence, computational linguistics, and information retrieval.