Abstract Summary
Since its inception in 2003, the various ImageCLEF challenges have provided large and complex datasets targeting a wide array of subjects in medicine, argumentation, reasoning, content recommendation, data generation, and question answering. In its 24th edition, ImageCLEF will have five main tasks: (i) a Medical task, which aims to promote the synergy between four medical challenges: Caption, involving concept detection and caption prediction in radiology images, Synthetic Medical Image Generation in the GANs task, Visual Question Answering for improving the diagnosis and classification of real medical gastrointestinal images, and multimodal dermatology response generation and a new MEDIQA-CORE challenge focusing on predicting or correcting tumor type labels and identifying and summarizing major and minor differences between pairs of radiology reports; (ii) the ToPicto task, involving text to pictogram translation and prediction, (iii) the Multimodal Reasoning task on visual, multi-language, interdisciplinary question answering, and 2 new tasks: (iv) AI4Agriculture, involving predicting agricultural potential before planing and crop type identification and (v) the Deepfake detection and generation task. In its last edition, 56 teams finished our challenges, continuing to show the impact in the community.
