{"url":"/dataset/medic","name":"MEDIC","full_name":null,"description_markdown":"**MEDIC** is a large social media image classification dataset for humanitarian response consisting of 71,198 images to address four different tasks in a multi-task learning setup. It consists data from several data sources such as [CrisisMMD](crisismmd), data from AIDR and Damage Multimodal Dataset (DMD).","description_withheld":null,"homepage":"https://github.com/firojalam/medic/","introduced_date":"2021-08-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/medic-a-multi-task-learning-dataset-for","title":"MEDIC: A Multi-Task Learning Dataset for Disaster Image Classification","first_author":"Firoj Alam","url":null},"license":{"name":"CC BY-NC-SA 4.0","url":"https://creativecommons.org/licenses/by-nc/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Disaster Response","url":"/task/disaster-response","datasets_with_task":"/datasets/task/disaster-response"}],"languages":[],"variants":["MEDIC"],"data_loaders":[{"repo":"https://github.com/firojalam/medic","url":"http://crisisnlp.qcri.org/medic/","frameworks":["pytorch"]}],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}