{"url":"/dataset/skinl2","name":"SKINL2","full_name":"Light Field Image Dataset of Skin Lesions","description_markdown":"The SKINL2 dataset comprises a total of 376 light fields acquired under similar conditions. The images were classified using eight categories, according to the type of skin lesion/ICD code: \r\n\r\n    Melanoma / C43\r\n    Melanocytic Nevus / D22\r\n    Basal Cell Carcinoma / D04\r\n    Seborrheic Keratosis / L82\r\n    Hemangioma / D18\r\n    Dermatofibroma / D23s\r\n    Psoriasis / L40\r\n    Other\r\n\r\nS. M. M. de Faria et al., \"Light Field Image Dataset of Skin Lesions,\" 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 3905-3908. DOI: 10.1109/EMBC.2019.8856578","description_withheld":null,"homepage":"https://www.it.pt/AutomaticPage?id=3459","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["SKINL2"],"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."}