{"url":"/dataset/disaster","name":"Disaster","full_name":null,"description_markdown":"**Disaster** is a dataset that contains images collected from various sources for three different disasters: fire, water and land. Besides this, it also contains images for various damaged infrastructure due to natural or man made calamities and damaged human due to war or accidents.\r\n\r\nThere are 13,720 manually annotated images in this dataset, each image is annotated by three individuals. The authors are also providing discriminating image class information annotated manually with bounding box for a set of 200 test images. Images are collected from different news portals, social media, and standard datasets made available by other researchers.","description_withheld":null,"homepage":"https://niloy193.github.io/Disaster-Dataset/","introduced_date":"2021-07-02","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-novel-disaster-image-dataset-and","title":"A Novel Disaster Image Dataset and Characteristics Analysis using Attention Model","first_author":"Fahim Faisal Niloy","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["Disaster"],"data_loaders":[],"num_papers_in_archive":1,"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."}