R. Borgo, B. Lee, B. Bach, S. Fabrikant, R. Jianu et al., Crowdsourcing for information visualization: Promises and pitfalls, Evaluation in the Crowd. Crowdsourcing and Human-Centered Experiments, pp.96-138, 2017.

D. Burghardt and M. Neun, Automated sequencing of generalisation services based on collaborative filtering, Geographic Information Science -4th International Conference GIScience, pp.41-46, 2006.

C. Duchêne, B. Baella, C. A. Brewer, D. Burghardt, B. P. Buttenfield et al., Generalisation in practice within national mapping agencies, Data Rich World, pp.329-391, 2014.

C. Duchêne, G. Touya, P. Taillandier, J. Gaffuri, A. Ruas et al., Multi-Agents systems for cartographic generalization: Feedback from past and ongoing research, 2018.

C. Cheng, Q. Liu, X. Li, W. , and Y. , Building simplification using backpropagation neural networks: a combination of cartographers' expertise and raster-based 1 https://github.com/IGNF/CartAGen local perception, GIScience & Remote Sensing, vol.50, issue.5, pp.527-542, 2013.

I. Goodfellow, J. Pouget-abadie, M. Mirza, B. Xu, D. Warde-farley et al., Generative adversarial nets, Advances in Neural Information Processing Systems, vol.27, pp.2672-2680, 2014.

D. Grünreich, Ein vorschlag zum aufbau einer grossmassstäbigen topographischkartographischenDatenbank unter besonderer berücksichtigung der grundrissdateides ALK-systems, Nachrichten aus dem Karten-und Vermessungswesen, Series I, vol.95, p.55, 1985.

L. E. Harrie, Weight-Setting and quality assessment in simultaneous graphic generalization, The Cartographic Journal, vol.40, issue.3, pp.221-233, 2003.

L. Harrie, H. Stigmar, and M. Djordjevic, Analytical estimation of map readability, ISPRS International Journal of Geo-Information, vol.4, issue.2, pp.418-446, 2015.

P. Isola, J. Zhu, T. Zhou, and A. A. Efros, Image-to-Image translation with conditional adversarial networks, 2017.

I. Karsznia and R. Weibel, Improving settlement selection for small-scale maps using data enrichment and machine learning, Cartography and Geographic Information Science, vol.45, issue.2, pp.111-127, 2018.

T. Kilpelainen, Knowledge acquisition for generalization rules, Cartography and Geographic Information Science, vol.27, issue.1, pp.41-50, 2000.

L. Landrieu and M. Simonovsky, Large-scale point cloud semantic segmentation with superpoint graphs, Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
URL : https://hal.archives-ouvertes.fr/hal-01801186

Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner, Gradient-based learning applied to document recognition, Proceedings of the IEEE, vol.86, issue.11, pp.2278-2324, 1998.

Y. Lecun, Y. Bengio, and G. Hinton, Deep learning, Nature, vol.521, issue.7553, pp.436-444, 2015.

L. Ma, Features extraction of buildings and generalization using deep learning, Proceedings of 28th International Cartographic Conference, 2017.

S. Mustière, J. Zucker, and L. Saitta, Abstraction-Based machine learning approach to cartographic generalisation, Proceedings of 9th International Symposium on Spatial Data Handling, vol.1, pp.50-63, 2000.

S. J. Pan, Y. , and Q. , A Survey on Transfer Learning, IEEE Transactions on Knowledge and Data Engineering, vol.22, issue.10, pp.1345-1359, 2010.

C. Plazanet, N. Bigolin, and A. Ruas, Experiments with learning techniques for spatial model enrichment and line generalization, vol.2, pp.315-333, 1998.

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

A. Ruas and C. Duchêne, A prototype generalisation system based on the Multi-Agent system paradigm, Generalisation of Geographic Information, pp.269-284, 2007.

M. Sester, Knowledge acquisition for the automatic interpretation of spatial data, International Journal of Geographical Information Science, vol.14, issue.1, pp.1-24, 2000.

M. Sester, Y. Feng, and F. Thiemann, Building generalization using deep learning. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp.565-572, 2018.

E. Simo-serra, S. Iizuka, K. Sasaki, and H. Ishikawa, Learning to simplify: Fully convolutional networks for rough sketch cleanup, ACM Transactions on Graphics, vol.35, issue.4, 2016.

S. Steiniger, T. Lange, D. Burghardt, and R. Weibel, An approach for the classification of urban building structures based on discriminant analysis techniques, Transactions in GIS, vol.12, issue.1, pp.31-59, 2008.

J. Stoter, D. Burghardt, C. Duchêne, B. Baella, N. Bakker et al., Methodology for evaluating automated map generalization in commercial software, Computers, Environment and Urban Systems, vol.33, issue.5, pp.311-324, 2009.

J. Stoter, X. Zhang, H. Stigmar, H. , and L. , Abstracting Geographic Information in a Data Rich World, Lecture Notes in Geoinformation and Cartography, pp.259-297, 2014.

C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed et al., Going deeper with convolutions, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1-9

P. Taillandier, C. Duchêne, and A. Drogoul, Automatic revision of rules used to guide the generalisation process in systems based on a trial and error strategy, International Journal of Geographical Information Science, vol.25, issue.12, pp.1971-1999, 2011.

G. Touya, A road network selection process based on data enrichment and structure detection, Transactions in GIS, vol.14, issue.5, pp.595-614, 2010.

G. Touya, Lessons learned from research on multimedia summarization, Proceedings of 18th ICA Workshop on Generalisation and Multiple Representation, 2015.

G. Touya, Vers l'automatisation de la production de cartes, 2017.

G. Touya and M. Dumont, Progressive block graying and landmarks enhancing as intermediate representations between buildings and urban areas, Proceedings of 20th ICA Workshop on Generalisation and Multiple Representation, 2017.
URL : https://hal.archives-ouvertes.fr/hal-02097486

G. Touya, B. Bucher, G. Falquet, K. Jaara, and S. Steiniger, Modelling geographic relationships in automated environments, Abstracting Geographic Information in a Data Rich World, pp.53-82, 2014.

B. Springer,

G. Touya, I. Lokhat, and C. Duchêne, CartAGen: an Open Source Research Platform for Map Generalization, 2019.

R. Weibel, S. Keller, and T. Reichenbacher, Overcoming the knowledge acquisition bottleneck in map generalization: The role of interactive systems and computational intelligence, Spatial Information Theory, A Theoretical Basis for GIS, pp.139-156, 1995.

Y. Xu, Z. Chen, Z. Xie, and L. Wu, Quality assessment of building footprint data using a deep autoencoder network, International Journal of Geographical Information Science, vol.31, issue.10, pp.1929-1951, 2017.

Q. Zhou and Z. Li, Empirical determination of geometric parameters for selective omission in a road network, International Journal of Geographical Information Science, vol.30, issue.2, pp.263-299, 2016.

Q. Zhou and Z. Li, A comparative study of various supervised learning approaches to selective omission in a road network, The Cartographic Journal, vol.54, issue.3, pp.254-264, 2017.