{"url":"/dataset/cifar10mnist","name":"Cifar10Mnist","full_name":null,"description_markdown":"The **Cifar10Mnist** dataset is created using CIFAR-10 and MNIST data sources. \r\nSince the CIFAR-10 training set consists of 50000 images and the MNIST training set contains 60000 digits, the first 50000 digits from MNIST are padded on top of the CIFAR-10 images after making them slightly translucent. A first training dataset is then obtained (50000 images). Furthermore, the remaining 10000 MNIST digits are padded on top of 10000 random CIFAR10 images (with a fixed seed). This gives the possibility of having a second training dataset of  60000 images. \r\nFor the test set, the 10000 CIFAR-10 images are padded over the 10000 MNIST digits.","description_withheld":null,"homepage":"","introduced_date":"2023-08-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/multi-objective-optimization-for-sparse-deep","title":"Multi-Objective Optimization for Sparse Deep Multi-Task Learning","first_author":"S. S. Hotegni","url":null},"license":{"name":"MIT License","url":"https://github.com/salomonhotegni/MDMTN/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Multi-Task Learning","url":"/task/multi-task-learning","datasets_with_task":"/datasets/task/multi-task-learning"},{"name":"Adversarial Attack","url":"/task/adversarial-attack","datasets_with_task":"/datasets/task/adversarial-attack"}],"languages":[],"variants":["Cifar10Mnist"],"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."}