{"url":"/dataset/rice-grains-brri","name":"Rice Grains BRRI","full_name":"Rice Grain Disease Dataset for False Smut and Neck Blast","description_markdown":"dataset (balanced) of 200 images consists of three classes - False Smut, Neck Blast and healthy grain class. Some of these images contain both diseases together. Field data collected under the supervision of staff from the Bangladesh Rice Research Institute (BRRI).","description_withheld":null,"homepage":"https://zenodo.org/record/7582108","introduced_date":"2020-04-21","introduced_date_note":null,"introduced_by":{"paper":"/paper/rice-grain-disease-identification-using-dual","title":"Rice grain disease identification using dual phase convolutional neural network based system aimed at small dataset","first_author":"Tashin Ahmed","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["Rice Grains BRRI"],"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."}