, OpenStreetMap contributors, 2017.

V. Mnih and G. Hinton, Learning to label aerial images from noisy data, ICML, 2012.

Z. Yu, W. Liu, Y. Zou, C. Feng, B. V. Srikumar-ramalingam et al., , 2018.

J. E. Vargas-muoz, D. Marcos, S. Lobry, J. A. Santos, A. X. Falco et al., Correcting misaligned rural building annotations in open street map using convolutional neural networks evidence, IGARSS, 2018.

N. Girard, G. Charpiat, and Y. Tarabalka, Aligning and updating cadaster maps with aerial images by multi-task, multi-resolution deep learning, ACCV, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01923568

O. Ronneberger, P. Fischer, and T. Brox, U-net: Convolutional networks for biomedical image segmentation, 2015.

E. Maggiori, Y. Tarabalka, G. Charpiat, and P. Alliez, Can semantic labeling methods generalize to any city? the Inria aerial image labeling benchmark, IGARSS, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01468452

K. Bradbury, B. Brigman, L. Collins, T. Johnson, S. Lin et al., Aerial imagery object identification dataset for building and road detection, and building height estimation, 2016.

J. Lehtinen, J. Munkberg, J. Hasselgren, S. Laine, T. Karras et al., Noise2noise: Learning image restoration without clean data, 2018.