{"url":"/dataset/lag","name":"LAG","full_name":"Large-scale Attention based Glaucoma","description_markdown":"Includes 5,824 fundus images labeled with either positive glaucoma (2,392) or negative glaucoma (3,432).\r\n\r\nSource: [Attention Based Glaucoma Detection: A Large-scale Database and CNN Model](/paper/attention-based-glaucoma-detection-a-large)","description_withheld":null,"homepage":"https://github.com/smilell/AG-CNN","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/attention-based-glaucoma-detection-a-large","title":"Attention Based Glaucoma Detection: A Large-scale Database and CNN Model","first_author":"Liu Li","url":null},"license":null,"modalities":[],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Anomaly Detection","url":"/task/anomaly-detection","datasets_with_task":"/datasets/task/anomaly-detection"}],"languages":[],"variants":["LAG"],"data_loaders":[{"repo":"https://github.com/smilell/AG-CNN","url":"https://github.com/smilell/AG-CNN","frameworks":[]}],"num_papers_in_archive":21,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/anomaly-detection-on-lag","task":"Anomaly Detection","dataset_variant":"LAG","rows":5,"metrics":["AUC"],"first_row_in_archive_order":{"model":"CCD","paper":"/paper/constrained-contrastive-distribution-learning","metrics":{"AUC":"0.874"},"code_links":[{"title":"tianyu0207/CCD","url":"https://github.com/tianyu0207/CCD"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/constrained-contrastive-distribution-learning","title":"Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images","date":"2021-03-05","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/unsupervised-anomaly-detection-and","title":"Deep One-Class Classification via Interpolated Gaussian Descriptor","date":"2021-01-25","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/padim-a-patch-distribution-modeling-framework","title":"PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization","date":"2020-11-17","rows_on_this_dataset":1,"code_links":26,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":7,"samples_unverified":0,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/panda-predicting-the-change-in-proteins","title":"PANDA: Predicting the change in proteins binding affinity upon mutations using sequence information","date":"2020-09-16","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/f-anogan-fast-unsupervised-anomaly-detection","title":"f-AnoGAN: Fast Unsupervised Anomaly Detection with Generative Adversarial Networks","date":"2019-01-30","rows_on_this_dataset":1,"code_links":3,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":8,"samples_ran":8,"samples_unverified":0,"pointer_only_for_licence":4,"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."}