{"url":"/dataset/mmcows","name":"MmCows","full_name":null,"description_markdown":"MmCows is a large-scale multimodal dataset for behavior monitoring, health management, and dietary management of dairy cattle.\r\n\r\nThe dataset consists of data from 16 dairy cows collected during a 14-day real-world deployment, divided into two modality groups. The primary group includes 3D UWB location, cows' neck IMMU acceleration, air pressure, cows' CBT, ankle acceleration, multi-view RGB images, indoor THI, outdoor weather, and milk yield. The secondary group contains measured UWB distances, cows' head direction, lying behavior, and health records.\r\n\r\nMmCows also contains 20,000 isometric-view images from multiple camera views in one day that are annotated with cows' ID and their behavior as the ground truth. The annotated cow IDs from multi-views are used to derive their 3D body location ground truth.","description_withheld":null,"homepage":"https://github.com/neis-lab/mmcows","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"CC BY-NC-SA 4.0","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["MmCows"],"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."}