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Exploring the hidden potential of common spatial data models to visualize uncertainty / J. Kardos in Cartography and Geographic Information Science, vol 32 n° 4 (October 2005)
[article]
Titre : Exploring the hidden potential of common spatial data models to visualize uncertainty Type de document : Article/Communication Auteurs : J. Kardos, Auteur ; Antoni B. Moore, Auteur ; G.L. Benwell, Auteur Année de publication : 2005 Article en page(s) : pp 359 - 367 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] arbre quadratique
[Termes IGN] incertitude des données
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] structure de données localisées
[Termes IGN] visualisationRésumé : (Auteur) Common Spatial Data Models (SDMs) such the vector, raster, and quadtree have well understood and widely practiced conventions of storage and visualization. This paper explores what happens when the conventions of visualization are not strictly adhered to, and the SDMs are used in an atypical fashion. A framework based on a quasi similarity measure is presented, which quantifies (in terras of "distance") the relationship between the storage format and the visualization output, following an accepted protocol. This research used a transformation process (Tp) to define this distance. Then, the atypical use of the quadtree SDM to represent choropleth spatial boundary uncertainty and attribute uncertainty was quantified using the same framework. This research shows that if a SDM is used outside of its original context, then the distance between the storage format and its visual output can alter; in our case, the distance decreased. This result was interpreted as evidence for the creation of a new spatial data structure. The formalization of the relationship between an SDM and its visual output will be valuable for future exploration of the non-conventional visualization of common SDMs. Numéro de notice : A2005-538 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1559/152304005775194827 En ligne : https://doi.org/10.1559/152304005775194827 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27674
in Cartography and Geographic Information Science > vol 32 n° 4 (October 2005) . - pp 359 - 367[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-05041 RAB Revue Centre de documentation En réserve L003 Disponible Cartographic generalization of roads in a local and adaptive approach: A knowledge acquistion problem / Sébastien Mustière in International journal of geographical information science IJGIS, vol 19 n° 8 - 9 (september 2005)
[article]
Titre : Cartographic generalization of roads in a local and adaptive approach: A knowledge acquistion problem Type de document : Article/Communication Auteurs : Sébastien Mustière , Auteur Année de publication : 2005 Article en page(s) : pp 937 - 955 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] acquisition de connaissances
[Termes IGN] algorithme d'apprentissage
[Termes IGN] algorithme de filtrage
[Termes IGN] analyse spatiale
[Termes IGN] apprentissage dirigé
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] moteur d'inférence
[Termes IGN] objet géographique linéaire
[Termes IGN] réseau routier
[Termes IGN] système expert
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) This paper presents a local and adaptive approach to road generalization, where different algorithms may be successively applied to each part of a road. The specific problem addressed is how to acquire and formalize cartographic knowledge in order to guide the application of the algorithms during the process. Our approach requires toolboxes of algorithms to transform and analyse the data, as well as an engine to chain them together. First, we present the toolboxes used in our experiments for road generalization. Then, we present two different engines, as well as the knowledge-acquisition processes used to determine them. The first engine, named GALBE, is an empirically determined process, where the application of algorithms is mainly based on a single criterion: the coalescence. The second engine, which is more complex, uses multiple measures to describe the road. The choice of which algorithm to use given a particular set of measures is determined from examples using supervised learning techniques. Results obtained with both engines are presented. Copyright Taylor & Francis Numéro de notice : A2005-408 Affiliation des auteurs : COGIT (1988-2011) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658810509161245 Date de publication en ligne : 20/02/2007 En ligne : https://doi.org/10.1080/13658810509161245 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27544
in International journal of geographical information science IJGIS > vol 19 n° 8 - 9 (september 2005) . - pp 937 - 955[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-05081 RAB Revue Centre de documentation En réserve L003 Disponible 079-05082 RAB Revue Centre de documentation En réserve L003 Disponible Automatic 3D object recognition and reconstruction based on neuro-fuzzy modelling / F. Samadzadegan in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 5 (August - October 2005)
[article]
Titre : Automatic 3D object recognition and reconstruction based on neuro-fuzzy modelling Type de document : Article/Communication Auteurs : F. Samadzadegan, Auteur ; A. Azizi, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 255 - 277 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] Allemagne
[Termes IGN] image aérienne
[Termes IGN] image en couleur
[Termes IGN] milieu urbain
[Termes IGN] raisonnement flou
[Termes IGN] reconnaissance automatique
[Termes IGN] reconnaissance d'objets
[Termes IGN] reconstruction 3D
[Termes IGN] réseau neuronal artificiel
[Termes IGN] visualisation 3DRésumé : (Auteur) Three-dimensional object recognition and reconstruction (ORR) is a research area of major interest in computer vision and photogrammetry. Virtual cities, for example, is one of the exciting application fields of ORR which became very popular during the last decade. Natural and man-made objects of cities such as trees and buildings are complex structures and automatic recognition and reconstruction of these objects from digital aerial images but also other data sources is a big challenge. In this paper, a novel approach for object recognition is presented based on neuro-fuzzy modelling. Structural, textural and spectral information is extracted and integrated in a fuzzy reasoning process. The learning capability of neural networks is introduced to the fuzzy recognition process by taking adaptable parameter sets into account which leads to the neuro-fuzzy approach. Object reconstruction follows recognition seamlessly by using the recognition output and the descriptors which have been extracted for recognition. A first successful application of this new ORR approach is demonstrated for the three object classes 'buildings', 'cars' and 'trees' by using aerial colour images of an urban area of the town of Engen in Germany. Copyright ISPRS Numéro de notice : A2005-351 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2005.02.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2005.02.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27487
in ISPRS Journal of photogrammetry and remote sensing > vol 59 n° 5 (August - October 2005) . - pp 255 - 277[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-05031 SL Revue Centre de documentation Revues en salle Disponible A statistical self-organizing learning system for remote sensing classification / H.M. Chi in IEEE Transactions on geoscience and remote sensing, vol 43 n° 8 (August 2005)
[article]
Titre : A statistical self-organizing learning system for remote sensing classification Type de document : Article/Communication Auteurs : H.M. Chi, Auteur ; O.K. Ersoy, Auteur Année de publication : 2005 Article en page(s) : pp 1890 - 1900 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] carte de Kohonen
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image hyperspectrale
[Termes IGN] méthode des moindres carrés
[Termes IGN] noeud
[Termes IGN] système expert
[Termes IGN] transformation non linéaireRésumé : (Auteur) A new learning system called a statistical self-organizing learning system (SSOLS), combining functional-link neural networks, statistical hypothesis testing, and self-organization of a number of enhancement nodes, is introduced for remote sensing applications. Its structure consists of two stages, a mapping stage and a learning stage. The input training vectors are initially mapped to the enhancement vectors in the mapping stage by multiplying with a random matrix, followed by pointwise nonlinear transformations. Starting with only one enhancement node, the enhancement layer incrementally adds an extra node in each iteration. The optimum dimension of the enhancement layer is determined by using an efficient leave-one-out cross-validation method. In this way, the number of enhancement nodes is also learned automatically. A t-test algorithm can also be applied to the mapping stage to mitigate the effect of overfitting and to further reduce the number of enhancement nodes required, resulting in a more compact network. In the learning stage, both the input vectors and the enhancement vectors are fed into a least squares learning module to obtain the estimated output vectors. This is made possible by choosing the output layer linear. In addition, several SSOLSs can be trained independently in parallel to form a consensual SSOLS, whose final output is a linear combination of the outputs of each SSOLS module. The SSOLS is simple, fast to compute, and suitable for remote sensing applications, especially with hyperspectral image data of high dimensionality. Numéro de notice : A2005-393 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2005.851188 En ligne : https://doi.org/10.1109/TGRS.2005.851188 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27529
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 8 (August 2005) . - pp 1890 - 1900[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-05081 RAB Revue Centre de documentation En réserve L003 Disponible Assessment of simulated cognitive maps: the influence of prior knowledge from cartographic maps / R.E. Lloyd in Cartography and Geographic Information Science, vol 32 n° 3 (July 2005)
[article]
Titre : Assessment of simulated cognitive maps: the influence of prior knowledge from cartographic maps Type de document : Article/Communication Auteurs : R.E. Lloyd, Auteur Année de publication : 2005 Article en page(s) : pp 161 - 179 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage dirigé
[Termes IGN] base de connaissances
[Termes IGN] carte cognitive
[Termes IGN] carte de Kohonen
[Termes IGN] congruence
[Termes IGN] représentation cartographique
[Termes IGN] représentation mentale spatiale
[Termes IGN] réseau neuronal artificiel
[Termes IGN] simulationRésumé : (Auteur) Real cognitive maps encoded by humans are difficult to study using experimental methods because they are a product of complex processes whose content and timing, cannot easily be known or controlled. This paper assesses the value of using neural network model simulations for investigating cognitive maps. The study simulated the learning of mapped city locations in South Carolina from reference sites in the three primary regions of the state using Kohonen selforganizing maps. The learning performances of models were considered based on available prior knowledge. Bi-dimensional regression analyses were used to assess the congruity of the simulated cognitive maps with a cartographic map and with sketch maps produced by human subjects. Error analyses indicated differences between central and peripheral reference sites. The cities known by subjects living at a central location were more evenly distributed in space and associated with significantly smaller errors. Models that learned combined state boundary and interstate highway information as prior knowledge or simultaneously with city locations consistently produced the best simulation results. The results indicated simulated cognitive maps could be used effectively to study the acquisition of spatial knowledge. Numéro de notice : A2005-417 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1559/1523040054738963 En ligne : https://doi.org/10.1559/1523040054738963 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27553
in Cartography and Geographic Information Science > vol 32 n° 3 (July 2005) . - pp 161 - 179[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-05031 RAB Revue Centre de documentation En réserve L003 Disponible vol 19 n° 4-5 - 2005-4 - Apprentissage automatique (Bulletin de Revue d'intelligence artificielle, RIA : Revue des Sciences et Technologies de l'Information, RSTI) / Michel LiquièrePermalinkNouvelle approche du réseau ARTMAP flou : application à la classification multi-spectrale des images SPOT XS de la baie d'Alger / F. Alilat in Revue Française de Photogrammétrie et de Télédétection, n° 177 (Juin 2005)PermalinkVisualizing demographic trajectories with self-organizing maps / A. Skupin in Geoinformatica, vol 9 n° 2 (June - August 2005)PermalinkNeural network model for standard PCA and its variants applied to remote sensing / S. Chitroub in International Journal of Remote Sensing IJRS, vol 26 n° 10 (May 2005)PermalinkIntegration of genetic algorithms and GIS for optimal location search / X. Li in International journal of geographical information science IJGIS, vol 19 n° 5 (may 2005)PermalinkAutomatic determination of the optimum generic sensor model based on genetic algorithm concepts / F. Samadzadegan in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 3 (March 2005)PermalinkNested hyper-rectangle learning model for remote sensing: land-cover classification / L. Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 3 (March 2005)PermalinkSparse grids: a new predictive modelling method for the analysis of geographic data / S.W. Laffan in International journal of geographical information science IJGIS, vol 19 n° 3 (march 2005)Permalink7e conférence francophone sur l'apprentissage automatique, CAp 2005, [Plate-forme AFIA], 30 mai - 3 juin 2005, Nice, France / François Denis (2005)Permalink7es Rencontres des Jeunes Chercheurs en Intelligence Artificielle [Plate-forme AFIA 2005] / Emmanuel Guéré (2005)PermalinkAAMAS'05, fifth European workshop on adaptive agents and multi-agent systems, March 21 - 22, 2005, Paris, France / Eduardo Alonso (2005)PermalinkMéthodologie d'évaluation de la cohérence interreprésentations pour l'intégration de bases de données spatiales / David Sheeren (2005)PermalinkRobust multiple estimator systems for the analysis of biophysical parameters from remotely sensed data / Lorenzo Bruzzone in IEEE Transactions on geoscience and remote sensing, vol 43 n° 1 (January 2005)PermalinkLa société de l'information et ses enjeux, actes du colloque de bilan du programme interdisciplinaire "Société de l'Information" 2001 - 2005, 19 - 21 mai 2005, Lyon, France / Jean-Louis Lebrave (2005)PermalinkData mining of cellular automata's transition rules / X. Li in International journal of geographical information science IJGIS, vol 18 n° 8 (december 2004)PermalinkExamination of a constant-area quadrilateral grid in representation of global digital elevation models / J.T. Bjorke in International journal of geographical information science IJGIS, vol 18 n° 7 (november 2004)PermalinkVicarious radiometric calibration of satellite ocean colour sensors / D. Antoine (01/09/2004)PermalinkSupporting quality-based image retrieval through user preference learning / Giorgos Mountrakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 8 (August 2004)PermalinkA split model for extraction of subpixel impervious surface information / Y. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 7 (July 2004)PermalinkThe characteristics and interpretability of land surface change and implications for project design / T.L. Sohl in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 4 (April 2004)PermalinkArtificial neural network-based techniques for the retrieval of SWE [snow water equivalent] and snow depth from SSM/I data / Marco Tedesco in Remote sensing of environment, vol 90 n° 1 (15/03/2004)PermalinkIntegrating imaging spectroscopy and neural networks to map grass quality in the Kruger National Park, South Africa / Onisimo Mutanga in Remote sensing of environment, vol 90 n° 1 (15/03/2004)PermalinkA hybrid texture segmentation method for mapping urban land use / Nezamoddin N. Kachouie in Geomatica, vol 58 n° 1 (March 2004)PermalinkUsing quadtree segmentation to support error modelling in categorical raster data / S. De Bruin in International journal of geographical information science IJGIS, vol 18 n° 2 (march 2004)PermalinkAn artificial neural network approach for landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas / M.K. Arora in International Journal of Remote Sensing IJRS, vol 25 n° 3 (February 2004)PermalinkToward universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements / G. Le Maire in Remote sensing of environment, vol 89 n° 1 (15/01/2004)PermalinkConsistency assessment between multiple representations of geographical databases: a specification-based approach / David Sheeren (2004)PermalinkA cost-effective semisupervised classifier approach with kernels / M. Murat Dundar in IEEE Transactions on geoscience and remote sensing, vol 42 n° 1 (January 2004)PermalinkDetecting building changes from multitemporal aerial stereopairs / Franck Jung in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 3-4 (January - June 2004)PermalinkExploration et utilisation d'ArcSDE / V. Bonnetain (2004)PermalinkFouille de données spatiales / Nadjim Chelghoum (2004)PermalinkModeling reality: how computers mirror life / Iwo Bialynicki-Birula (2004)PermalinkObject-based classification of remote sensing data for change detection / Volker Walter in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 3-4 (January - June 2004)PermalinkVers une réconciliation des experts et des systèmes : expériences d’utilisation de méthodes d’apprentissage automatique pour la généralisation et l’intégration des bases de données géographiques / Sébastien Mustière (2004)PermalinkClassification of wheat crop with multi-temporal images: performance of maximum likelihood and artificial neural networks / C.S. Murthy in International Journal of Remote Sensing IJRS, vol 24 n° 23 (December 2003)PermalinkTraining a neural network with a canopy reflectance model to estimate crop leaf area index / F. Mark Danson in International Journal of Remote Sensing IJRS, vol 24 n° 23 (December 2003)PermalinkA cognitive pyramid for contextual classification of remote sensing images / E. Binaghi in IEEE Transactions on geoscience and remote sensing, vol 41 n° 12 (December 2003)PermalinkKnowledge discovery from soil maps using inductive learning / F. Qi in International journal of geographical information science IJGIS, vol 17 n° 8 (december 2003)PermalinkBayesian classification by data augmentation / B. Regguzoni in International Journal of Remote Sensing IJRS, vol 24 n° 20 (October 2003)PermalinkA neural adaptive model for feature extraction and recognition in high resolution remote sensing imagery / E. Binaghi in International Journal of Remote Sensing IJRS, vol 24 n° 20 (October 2003)PermalinkICEAGE: interactive clustering and exploration of large and high-dimensional geodata / D. Guo in Geoinformatica, vol 7 n° 3 (September - November 2003)PermalinkInfometric and statistical diagnostics to provide artificially-intelligent support for spatial analysis: the example of interpolation / C.H. Jarvis in International journal of geographical information science IJGIS, vol 17 n° 6 (september 2003)PermalinkSimulation of development alternatives using neural networks, cellular automata, and GIS for urban planning / A.G. Yeh in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)Permalinkvol 17 n° 5-6 - 2003-5 - Regard croisés sur l'analogie (Bulletin de Revue d'intelligence artificielle, RIA : Revue des Sciences et Technologies de l'Information, RSTI) / Karine DuvignauPermalinkWater quality retrievals from combined Landsat TM data and ERS-2 SAR data in the Gulf of Finland / Y. Zhang in IEEE Transactions on geoscience and remote sensing, vol 41 n° 3 (March 2003)PermalinkJNRR'03, quatrièmes journées nationales de recherche en robotique, 8 - 10 Octobre 2003, Clermont-Ferrand, France / Philippe Bidaud (2003)PermalinkPermalinkSpatial databases integration : interpretation of multiple representations by using machine learning techniques / David Sheeren (2003)PermalinkUtilisation de connaissances d'experts pour l'automatisation de la caractérisation des alignemnts de bâtiments / Anne Ruas (2003)PermalinkLe boosting : une méthode de classification non paramétrique / Michel Arnaud in Revue internationale de géomatique, vol 12 n° 4 (décembre 2002 – février 2003)PermalinkCalibration of stochastic cellular automata: the application to rural-urban land conversions / F. Wu in International journal of geographical information science IJGIS, vol 16 n° 8 (december 2002)PermalinkLe procédé de navigation spatiale Transmap (R) : application à l'imagerie territoriale / Franck Perdrizet in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 168 (Octobre 2002)PermalinkL'appariement pour la constitution de bases de données géographiques multirésolutions. Vers une interprétation des différences de représentation / David Sheeren in Revue internationale de géomatique, vol 12 n° 2 (juin - août 2002)PermalinkNeural-network-based cellular automata for simulating multiple land use changes using GIS / X. Li in International journal of geographical information science IJGIS, vol 16 n° 4 (june 2002)PermalinkAutomated photogrammetric network design using genetic algorithms / G. Olague in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 5 (Mai 2002)PermalinkArtificial neural networks as a method of spatial interpolation for digital elevation models / D.A. Merwin in Cartography and Geographic Information Science, vol 29 n° 2 (April 2002)PermalinkDétection de changements par comparaison de couples stéréoscopiques / Franck Jung in Géomatique expert, n° 15 (01/04/2002)PermalinkL'appariement pour la constitution de bases de données géographiques multi-résolutions / David Sheeren (2002)PermalinkECAI 2002, 15th European Conference on Artificial Intelligence, July 21-26, Lyon, France / Frank Van Harmelen (2002)PermalinkGénéralisation et représentation multiple / Anne Ruas (2002)PermalinkGénéralisation et représentation multiple, ch. 20. Généralisation cartographique et apprentissage automatique à partir d'exemples / Sébastien Mustière (2002)PermalinkVision with non-traditional sensors, 26th workshop of the Austrian Association for Pattern Recognition (ÖAGM/AAPR), Graz, September 10 - 11, 2002 / Franz W. Leberl (2002)PermalinkWorkshop 12 Knowledge discovery from temporal and spatial data / Christophe Dousson (2002)PermalinkRetrieval of sea water optically active parameters from hyperspectral data by means of generalized radial basis function neural networks / P. Cipollini in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)PermalinkArtificial neural networks as a tool for spatial interpolation / J.P. Rigol in International journal of geographical information science IJGIS, vol 15 n° 4 (june 2001)PermalinkA neural network image interpretation system to extract rural and urban land use and land cover information from remote sensor data / J.R. Jensen in Geocarto international, vol 16 n° 1 (March - May 2001)PermalinkPermalinkComparison of different approaches to combine road generalisation algorithms: GALBE, AGENT and CartoLearn / Sébastien Mustière (2001)PermalinkContrôle de la qualité d'une base de données géographiques / Carlos Goncalves (2001)PermalinkPermalinkFifth ICA workshop on progress in automated map generalization, August 2 - 4, 2001, Beijing, China / Commission on map generalization ICA (2001)PermalinkGeoComputational modelling / Manfred M. Fischer (2001)PermalinkMapping the 21st century: the 20th International Cartographic Conference, ICC 2001, Beijing, China, August 6 - 10, 2001, vol 2. Proceedings / L. Li (2001)PermalinkPermalinkReconnaissance d'objets par focalisation et détection de changement / Franck Jung (2001)PermalinkSpatial databases : with applications to GIS / Philippe Rigaux (2001)PermalinkSpatial prediction of fire ignition probabilities: comparing logistic regression and neural networks / M.J. Perestrello De Vasconcelos in Photogrammetric Engineering & Remote Sensing, PERS, vol 67 n° 1 (January 2001)PermalinkAbstraction et changement de langage pour automatiser la généralisation cartographique / Sébastien Mustière (2000)PermalinkJournées data mining spatial et analyse du risque, Versailles, 24 - 25 février 2000 / Sylvain Lassarre (2000)PermalinkMachine learning techniques for determining parameters of cartographic generalisation algorithms / Lagrange (Enseigne de Vaisseau) (2000)PermalinkOptimising generalisation sequences using machine learning techniques / Nicolas Regnauld (2000)PermalinkPermalinkAdvanced polarimetric SAR data classification for cartographic information extraction / Manfred F. Buchroithner (31/05/1999)PermalinkApprentissage automatique / Marc Sebban (1999)PermalinkBeschreibung von Deformationsprozessen durch Volterra- und Fuzzy-Modelle sowie neuronale Netze / K. Heine (1999)PermalinkConférence d'apprentissage 99, actes de CAP'99, Ecole Polytechnique, Palaiseau, 15-18 juin 1999 / Michèle Sebag (1999)PermalinkElectromagnetic optimization by genetic algorithms / Yahya Rahmat-Samii (1999)PermalinkExperiments with Learning Techniques for Spatial Model Enrichment and Line Generalization / Corinne Plazanet in Geoinformatica, vol 2 n° 4 (December 1998)PermalinkThe ASTER polar cloud mask / A.M. Logar in IEEE Transactions on geoscience and remote sensing, vol 36 n° 4 (July 1998)PermalinkAnalyse d'images aériennes haute résolution : détection et modélisation du bâti en zone urbaine / Matthieu Cord (1998)PermalinkExtraction, par apprentissage supervisé, de textures sur cartes géographiques / Robert Mariani in Bulletin d'information de l'Institut géographique national, n° 68 (octobre 1997)PermalinkLes agents intelligents / Jean Sallantin (1997)PermalinkContribution à la lecture automatique de cartes / Robert Mariani (1997)PermalinkTriangulation de Delaunay et arbres multidimensionnels / Christophe Lemaire (1997)PermalinkUsing genetic learning neural networks for spatial decision making in GIS / J. Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 62 n° 11 (november 1996)Permalink