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Constraint based evaluation of generalized images generated by deep learning / Azelle Courtial (2020)
Titre : Constraint based evaluation of generalized images generated by deep learning Type de document : Article/Communication Auteurs : Azelle Courtial , Auteur ; Guillaume Touya , Auteur ; Xiang Zhang, Auteur Editeur : ICA Commission on Generalisation and Multiple Representation Année de publication : 2020 Projets : 1-Pas de projet / Conférence : ICA 2020, 23rd Workshop on Map Generalisation and Multiple Representation 05/11/2020 06/11/2020 Delft Pays-Bas Open Access Proceedings Importance : 3 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Français (fre) Descripteur : [Termes IGN] 1:25.000
[Termes IGN] 1:250.000
[Termes IGN] Alpes (France)
[Termes IGN] apprentissage profond
[Termes IGN] carte routière
[Termes IGN] classification pixellaire
[Termes IGN] données maillées
[Termes IGN] généralisation automatique de données
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] montagne
[Termes IGN] précision cartographique
[Termes IGN] programmation par contraintes
[Termes IGN] réseau routier
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) The use of deep learning techniques for map generalisation raises new problems regarding the evaluation of the results: (1) images are used as input/output instead of vector data; (2) the deep learning processes do not guarantee results that follow cartographic principles; (3) the deep learning models are black boxes that hide the causal mechanisms. Also, deep learning intern evaluation is mostly based on the realism of the images and the pixel classification accuracy, and none of these criteria is sufficient to evaluate a generalisation process. In this article, we propose an adaptation of the constraint-based evaluation to the images generated by deep learning. Six raster-based constraints are proposed for a mountain road generalisation use case. Numéro de notice : C2020-018 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans Date de publication en ligne : 17/11/2020 En ligne : https://varioscale.bk.tudelft.nl/events/icagen2020/ICAgen2020/ICAgen2020_paper_2 [...] Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96380 Is deep learning the new agent for map generalization? / Guillaume Touya in International journal of cartography, vol 5 n° 2-3 (July - November 2019)
[article]
Titre : Is deep learning the new agent for map generalization? Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Xiang Zhang, Auteur ; Imran Lokhat , Auteur Année de publication : 2019 Projets : 1-Pas de projet / Conférence : ICC 2019, 29th International Cartographic Conference ICA, Mapping everything for everyone 15/07/2019 20/07/2019 Tokyo Japon Open Access Proceedings of the ICA Article en page(s) : pp 142 - 157 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] système multi-agents
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) The automation of map generalization has been keeping researchers in cartography busy for years. Particularly great progress was made in the late 90s with the use of the multi-agent paradigm. Although the current use of automatic processes in some national mapping agencies is a great achievement, there are still many unsolved issues and research seems to stagnate in the recent years. With the success of deep learning in many fields of science, including geographic information science, this paper poses the controversial question of the title: is deep learning the new agent, i.e. the technique that will make generalization research bridge the gap to fully automated generalization processes? The paper neither responds a clear yes nor a clear no but discusses what issues could be tackled with deep learning and what the promising perspectives. Some preliminary experiments with building generalization or data enrichments are presented to support the discussion. Numéro de notice : A2019-235 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2019.1613071 Date de publication en ligne : 09/05/2019 En ligne : https://doi.org/10.1080/23729333.2019.1613071 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92932
in International journal of cartography > vol 5 n° 2-3 (July - November 2019) . - pp 142 - 157[article]Automatic derivation of on-demand tactile maps for visually impaired people: first experiments and research agenda / Guillaume Touya in International journal of cartography, vol 5 n° 1 (March 2019)
[article]
Titre : Automatic derivation of on-demand tactile maps for visually impaired people: first experiments and research agenda Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Sidonie Christophe , Auteur ; Jean-Marie Favreau, Auteur ; Mohamed Amine Ben Rhaiem, Auteur Année de publication : 2019 Projets : 1-Pas de projet / Article en page(s) : pp 67 - 91 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] automatisation
[Termes IGN] carte sur mesure
[Termes IGN] carte tactile
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] impression 3D
[Termes IGN] personne malvoyante
[Termes IGN] style cartographique
[Vedettes matières IGN] GénéralisationRésumé : (auteur) Tactile maps are essential tools for visually impaired people to comprehend space and to support the simple pedestrian trips made difficult by their disability. Tactile maps are created manually and printed by specialists, and it takes a large amount of time to create a new one, which prevents using them on demand for everyday use. As a consequence, researchers and cartographers try to automate this creation process, but the existing automated derivation processes do not include generalization or advanced stylization steps, which limits their effectiveness. This paper reports first experiments to include such complex automated cartography processes to provide on-demand tactile maps for visually impaired people. These first experiments were more intended to raise real research issues than solve them, and the paper discusses these issues in a research agenda to achieve automatically derived tactile maps. Numéro de notice : A2019-379 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2018.1486784 Date de publication en ligne : 07/08/2018 En ligne : https://doi.org/10.1080/23729333.2018.1486784 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90797
in International journal of cartography > vol 5 n° 1 (March 2019) . - pp 67 - 91[article]
Titre : CartAGen: an open source research platform for map generalization Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Imran Lokhat , Auteur ; Cécile Duchêne , Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2019 Autre Editeur : Göttingen : Copernicus publications Collection : Proceedings of the ICA Projets : 1-Pas de projet / Conférence : ICC 2019, 29th International Cartographic Conference ICA, Mapping everything for everyone 15/07/2019 20/07/2019 Tokyo Japon Open Access Proceedings of the ICA Importance : 9 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de généralisation
[Termes IGN] CartAGen (plateforme de généralisation)
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] logiciel libre
[Termes IGN] organisme cartographique national
[Termes IGN] plateforme logicielle
[Termes IGN] système multi-agents
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Automatic map generalization is a complex task that is still a research problem and requires the development of research prototypes before being usable in productive map processes. In the meantime, reproducible research principles are becoming a standard. Publishing reproducible research means that researchers share their code and their data so that other researchers might be able to reproduce the published experiments, in order to check them, extend them, or compare them to their own experiments. Open source software is a key tool to share code and software, and CartAGen is the first open source research platform that tackles the overall map generalization problem: not only the building blocks that are generalization algorithms, but also methods to chain them, and spatial analysis tools necessary for data enrichment. This paper presents the CartAGen platform, its architecture and its components. The main component of the platform is the implementation of several multi-agent based models of the literature such as AGENT, CartACom, GAEL, CollaGen, or DIOGEN. The paper also explains and discusses different ways, as a researcher, to use or to contribute to CartAGen. Numéro de notice : C2019-010 Affiliation des auteurs : LASTIG COGIT (2012-2019) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-proc-2-134-2019 Date de publication en ligne : 10/07/2019 En ligne : https://doi.org/10.5194/ica-proc-2-134-2019 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93258 Documents numériques
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CartAGen: an open source research platform - pdf éditeurAdobe Acrobat PDF
Titre : Finding the oasis in the desert fog? Understanding multi-scale map reading Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2019 Projets : 1-Pas de projet / Conférence : ICC 2019 Workshop on Abstraction, Scale and Perception 15/07/2019 15/07/2019 Tokyo France Open Access Proceedings Importance : 3 p. Note générale : Bibliographie
sur HAL https://hal.archives-ouvertes.fr/hal-02266373Langues : Anglais (eng) Descripteur : [Termes IGN] échelle cartographique
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] représentation mentale spatiale
[Termes IGN] représentation multiple
[Termes IGN] zoom
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Fluid interactions of complex information visualizations promote flow by giving “a sense of control” and a loss of self-consciousness” during the interaction (Elmqvist et al., 2011).In the context of multi-scale geovisualization with different maps rendered at different zoom levels, fluid interactions mainly consist in smoothly zooming in the scales/zoom levels, while keeping a constant sense of place. User experience shows that current multi-scale maps are not provided with fluid interactions. Despite recent improvements, zooming in and out of multi-scale maps such as GoogleMaps, OSM, or National Mapping Agencies’ geoportals still causes a desert fog effect (Jul & Furnas, 1998) when the map changes. Desert fog can be defined as “a condition wherein a view of an information world contains no information on which to base navigational decisions.” In a multi-scale map, it means that the abstraction, content and style changes between two maps at different scales make the user lose his sense of place for a short moment wondering where his previous position (i.e. where he was looking at, or where his cursor was) is in the newly rendered map (Dumont et al., 2016). Contributions on continuous generalisation (van Oosterom et al., 2014), or on progressive generalisation (Dumont et al., 2017; Touya & Dumont, 2017) try to provide more continuous or progressive abstractions of map features across scales. [...] Numéro de notice : C2019-019 Affiliation des auteurs : LASTIG COGIT (2012-2019) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans Date de publication en ligne : 14/08/2019 En ligne : https://hal.science/hal-02266373 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93598 Documents numériques
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Finding the oasis in the desert fog? - pdf éditeurAdobe Acrobat PDF On the spatial distribution of buildings for map generalization / Zhiwei Wei in Cartography and Geographic Information Science, Vol 45 n° 6 (November 2018)PermalinkMeasured and perceived visual complexity : a comparative study among three online map providers / Susan Schnur in Cartography and Geographic Information Science, Vol 45 n° 3 (May 2018)PermalinkRecognizing building groups for generalization : a comparative study / Min Deng in Cartography and Geographic Information Science, Vol 45 n° 3 (May 2018)PermalinkLabelling hierarchy for street maps using centrality measures / Wasim Shoman in Cartographic journal (the), vol 55 n° 1 (February 2018)PermalinkA typification method for linear pattern in urban building generalisation / Xianyong Gong in Geocarto international, vol 33 n° 2 (February 2018)PermalinkGénéralisation de représentations intermédiaires dans une carte topographique multi-échelle pour faciliter la navigation de l’utilisateur / Marion Dumont (2018)PermalinkMulti-agents systems for cartographic generalization: Feedback from past and on-going research / Cécile Duchêne (2018)PermalinkBinSq : visualizing geographic dot density patterns with gridded maps / Alvin Chua in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)PermalinkDIOGEN, a multi-level oriented model for cartographic generalization / Adrien Maudet in International journal of cartography, vol 3 n° 1 (June 2017)PermalinkThe bounds of distortion : truth, meaning and efficacy in digital geographic representation / Lucas Godfrey in International journal of cartography, vol 3 n° 1 (June 2017)PermalinkVariable-scale maps in real-time generalisation using a quadtree data structure and space deforming algorithms / Pia Bereuter in International journal of cartography, vol 3 n° 1 (June 2017)PermalinkPermalinkThe International Encyclopedia of Geography: People, The Earth, Environment, and Technology, ch. Map Generalization / William A Mackaness (2017)PermalinkPermalinkClutter and map legibility in automated cartography : a research agenda / Guillaume Touya in Cartographica, vol 51 n° 4 (Winter 2016)PermalinkFourier-based multi-scale representation and progressive transmission of cartographic curves on the internet / Pengcheng Liu in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)PermalinkHow many samples are needed? An investigation of binary logistic regression for selective omission in a road network / Qi Zhou in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)PermalinkA Topology-inferred graph-based heuristic algorithm for map simplification / QiuLei Guo in Transactions in GIS, vol 20 n° 5 (October 2016)PermalinkEnhancing building footprints with squaring operations / Imran Lokhat in Journal of Spatial Information Science (JoSIS), n° 13 (September 2016)PermalinkAn immune genetic algorithm to buildings displacement in cartographic generalization / Yageng Sun in Transactions in GIS, vol 20 n° 4 (August 2016)Permalink