Following the recent evolutions of cartography, and a successful workshop in 2022 on Computational Cartography
and Map Generalisation with Deep Learning, this CartoAI workshop seeks to gather the researchers working on
artificial intelligence techniques applied to cartography. For this workshop, contributions on all AI
techniques are welcome including, e.g., machine learning, optimization, and multi-agent systems.
The workshop will give the opportunity to the participants to give short presentations of recent and on-going research. It will also include a keynote and time for discussions.
You are invited to submit a 2-page abstract, following the general guidelines of the ICA conference abstracts. The proceedings of the workshop will be published on the website of the ICA commission on map generalisation. Papers should be submitted to EasyChair. The following topics are welcome:
Workshop Program (09:00 - 12:30 BST)
Digging deep in history: Can we learn from the past to inform present and future AI models of map generalization?
-   Azelle Courtial, Jérémy Kalsron, Bérénice Le Mao, Quentin Potié, Guillaume Touya and Laura Wenclik.
Text-to-map generation: a review of current potentials (abstract)
-   Quentin Potié, Guillaume Touya and William Mackaness.
Experiments in the automatic segmentation of anchors using deep learning techniques (abstract)
-   Lawrence Stanislawski, Nattapon Jaroenchai, Shaowen Wang, Ethan Shavers, Alexander Duffy, Phillip Thiem, Zhe Jiang and Adam Camerer.
Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska (abstract)
-   Yuhao Kang, Song Gao and Robert Roth.
Artificial Intelligence Studies in Cartography: A Review and Synthesis of Methods, Applications, and Ethics (abstract)
-   Rachid Oucheikh and Lars Harrie. (Video presentation)
Design, implementation and evaluation of generative deep learning models for map labeling (abstract)
-   Lingrui Yan, Tinghua Ai, Aji Gao and Junbo Yu. (Video presentation)
Relief Shading Generation under Generative Adversarial Nets Considering Artistic Style Transfer (abstract)
-   Nicolas Beglinger, Zhiyong Zhou, Cheng Fu and Robert Weibel.
Vector road generalization using deep learning: An empirical study (abstract)
-   Yu Feng.
Prompt-aided Map Generalization with Diffusion Models (abstract)
-   Eric Lafon, Quentin Potié and Guillaume Touya.
Salient building detection using multimodal deep learning (abstract)
-   Iga Ajdacka and Izabela Karsznia.
The use of machine learning to automate the selection of rivers for small-scale maps (abstract)
-   Barry Kronenfeld, Lawrence Stanislawski, Barbara Buttenfield and Ethan Shavers. (Video presentation)
Generalization quality metrics to support multiscale mapping: Hausdorff and average distance between polylines (abstract)
-   Aji Gao, Tinghua Ai, Haosheng Huang, Junbo Yu and Huafei Yu. (Video presentation)
A Deep Learning Approach to 3D Building Map Generalization Based on Graph Convolutional Networks (abstract)
Azelle Courtial, IGN, Univ. Gustave Eiffel
Yuhao Kang, University of Wisconsin-Madison
Liqiu Meng, Technical University of Munich
Monika Sester, Leibniz University Hannover
Robert Weibel, University of Zurich
This workshop is kindly supported by the ICA Commission on Generalisation and Multiple Representation