Track 2: Unsupervised Domain Adaptation
This task is focused on unsupervised domain
adaptation methods, in which we provide unlabeled data from a target domain: the new Safran-
MNIST-DLS dataset, which comprises images of 32 classes depicting numbers, alphabetic characters, and symbols, namely:
[0, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, A, B, C, D, E, F, G, H, J, K, L, M, N, P, R, S, T, U, W, Y, /, .].
Participants are granted the freedom to use any publicly available data as of April 26, 2024 or generated data from various source domains.
Nonetheless, we provide a noncomprehensive list of datasets representing letters, digits and symbols, which participants may utilize,
namely: MNIST, MNIST-M, SVHN, HASYv2, Synthetic Digits, EMNIST (Extended MNIST), CROHME.
Proprietary data is not allowed.