{"url":"/dataset/fbis-22m","name":"FBIS-22M","full_name":"Field Boundary Instance Segmentation - 22M","description_markdown":"**FBIS-22M** is the largest field boundary instance segmentation dataset to date, featuring over 22 million labeled field instances across more than 672 000 high-resolution satellite image patches. It includes imagery from 0.25m to 10m resolution, sourced from multiple satellites and covering diverse geographic regions, enabling robust training for scalable agricultural vision models.","description_withheld":null,"homepage":"https://lavreniuk.github.io/Delineate-Anything/","introduced_date":"2025-04-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/delineate-anything-resolution-agnostic-field","title":"Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite Imagery","first_author":"Mykola Lavreniuk","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Field Boundary Delineation","url":"/task/field-boundary-delineation","datasets_with_task":"/datasets/task/field-boundary-delineation"}],"languages":[],"variants":["FBIS-22M"],"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."}