{"url":"/dataset/rit-18","name":"RIT-18","full_name":null,"description_markdown":"The RIT-18 dataset was built for the semantic segmentation of remote sensing imagery. It was collected with the Tetracam Micro-MCA6 multispectral imaging sensor flown on-board a DJI-1000 octocopter. \r\n\r\nThe features this dataset include 1) very-high resolution multispectral imagery from a drone, 2) six-spectral VNIR bands, and 3) 18 object classes (plus background) with a severely unbalanced class distribution.\r\n\r\nSource: [Algorithms for Semantic Segmentation of Multispectral Remote Sensing Imagery using Deep Learning](/paper/algorithms-for-semantic-segmentation-of)\r\nImage Source: [https://github.com/rmkemker/RIT-18](https://github.com/rmkemker/RIT-18)","description_withheld":null,"homepage":"https://github.com/rmkemker/RIT-18","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/algorithms-for-semantic-segmentation-of","title":"Algorithms for Semantic Segmentation of Multispectral Remote Sensing Imagery using Deep Learning","first_author":"Ronald Kemker","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Hyperspectral images","url":"/datasets/modality/hyperspectral-images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Object Recognition","url":"/task/object-recognition","datasets_with_task":"/datasets/task/object-recognition"}],"languages":[],"variants":["RIT-18"],"data_loaders":[{"repo":"https://github.com/rmkemker/RIT-18","url":"https://github.com/rmkemker/RIT-18","frameworks":[]}],"num_papers_in_archive":8,"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."}