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Allowing context to speak: the progressive case study method for cadastral systems research / Simon Hull in Survey review, vol 55 n° 390 (May 2023)  

Public [article]  inSurvey review > vol 55 n° 390 (May 2023) . - pp 205 - 215 Titre : Allowing context to speak: the progressive case study method for cadastral systems research Type de document : Article/Communication Auteurs : Simon Hull, Auteur ; Jennifer Whittal, Auteur Année de publication : 2023 Article en page(s) : pp 205 - 215 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre [Termes IGN] droit coutumier [Termes IGN] droit foncier [Termes IGN] prise en compte du contexte [Termes IGN] raisonnement déductif [Termes IGN] raisonnement inductif Résumé : (auteur) For research involving customary land rights, "context is key" because every context brings specific nuances for consideration. Failure to account for context runs the risk of irrelevance, unintended consequences and/or failure. We present a research method that allows context to speak: the progressive case study. The approach combines deductive case study with inductive grounded theory approaches. The results are used to propose a framework for guiding cadastral systems development in customary land rights contexts. This paper presents the methodology, which should be useful for researchers, NGOs and multinational organisations doing development programming in developing contexts. Numéro de notice : A2023-211 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/00396265.2022.2045457 Date de publication en ligne : 06/03/2022 En ligne : https://doi.org/10.1080/00396265.2022.2045457 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103065 [article]

A world model enabling information integrity for autonomous vehicles / Corentin Sanchez (2022)  

Public Titre : A world model enabling information integrity for autonomous vehicles Type de document : Thèse/HDR Auteurs : Corentin Sanchez, Auteur ; Philippe Bonnifait, Directeur de thèse ; Philippe Xu, Directeur de thèse Editeur : Compiègne : Université de Technologie de Compiègne UTC Année de publication : 2022 Importance : 198 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse de Doctorat de l'Université de Technologie de Compiègne, Spécialité Automatique et Robotique Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] attention (apprentissage automatique) [Termes IGN] carte routière [Termes IGN] données multisources [Termes IGN] information sémantique [Termes IGN] intégrité des données [Termes IGN] milieu urbain [Termes IGN] navigation autonome [Termes IGN] raisonnement [Termes IGN] réseau routier [Termes IGN] robot mobile [Termes IGN] sécurité routière [Termes IGN] véhicule sans pilote [Termes IGN] vision par ordinateur Index. décimale : THESE Thèses et HDR Résumé : (auteur) To drive in complex urban environments, autonomous vehicles need to understand their driving context. This task, also known as the situation awareness, relies on an internal virtual representation of the world made by the vehicle, called world model. This representation is generally built from information provided by multiple sources. High definition navigation maps supply prior information such as road network topology, geometric description of the carriageway, and semantic information including traffic laws. The perception system provides a description of the space and of road users evolving in the vehicle surroundings. Conjointly, they provide representations of the environment (static and dynamic) and allow to model interactions. In complex situations, a reliable and non-misleading world model is mandatory to avoid inappropriate decision-making and to ensure safety. The goal of this PhD thesis is to propose a novel formalism on the concept of world model that fulfills the situation awareness requirements for an autonomous vehicle. This world model integrates prior knowledge on the road network topology, a lane-level grid representation, its prediction over time and more importantly a mechanism to control and monitor the integrity of information. The concept of world model is present in many autonomous vehicle architectures but may take many various forms and sometimes only implicitly. In some work, it is part of the perception process when in some other it is part of a decisionmaking process. The first contribution of this thesis is a survey on the concept of world model for autonomous driving covering different levels of abstraction for information representation and reasoning. Then, a novel representation is proposed for the world model at the tactical level combining dynamic objects and spatial occupancy information. First, a graph based top-down approach using a high-definition map is proposed to extract the areas of interests with respect to the situation from the vehicle's perspective. It is then used to build a Lane Grid Map (LGM), which is an intermediate space state representation from the ego-vehicle point of view. A top-down approach is chosen to assess and characterize the relevant information of the situation. Additionally to classical free-occupied states, the unknown state is further characterized by the notions of neutralized and safe areas that provide a deeper level of understanding of the situation. Another contribution to the world model is an integrity management mechanism that is built upon the LGM representation. It consists in managing the spatial sampling of the grid cells in order to take into account localization and perception errors and to avoid misleading information. Regardless of the confidence on localization and perception information, the LGM is capable of providing reliable information to decision making in order not to take hazardous decisions.The last part of the situation awareness strategy is the prediction of the world model based on the LGM representation. The main contribution is to show how a classical object-level prediction fits this representation and that the integrity can also be extended at the prediction stage. It is also depicted how a neutralized area can be used in the prediction stage to provide a better situation prediction. The work relies on experimental data in order to demonstrate a real application of a complex situation awareness representation. The approach is evaluated with real data obtained thanks to several experimental vehicles equipped with LiDAR sensors and IMU with RTK corrections in the city of Compi_egne. A high-definition map has also been used in the framework of the SIVALab joint laboratory between Renault and Heudiasyc CNRS-UTC. The world model module has been implemented (with ROS software) in order to fulfll real-time application and is functional on the experimental vehicles for live demonstrations. Note de contenu : General introduction 1- World model for autonomous vehicules 2- An architecture for WM 3- A lane level world model 4- Set-based LGM prediction General conclusion Numéro de notice : 24089 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Automatique et Robotique : UTC Compiègne : 2022 Organisme de stage : Laboratoire Heudiasyc DOI : sans En ligne : https://www.theses.fr/2022COMP2683 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102509

Cartographic inference: a peircean perspective / Gordon A. Cromley in Cartographica, vol 55 n° 2 (Summer 2020)  

Public [article]  inCartographica > vol 55 n° 2 (Summer 2020) . - pp 124 - 135 Titre : Cartographic inference: a peircean perspective Type de document : Article/Communication Auteurs : Gordon A. Cromley, Auteur Année de publication : 2020 Article en page(s) : pp 124 - 135 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie [Termes IGN] carte analytique [Termes IGN] inférence [Termes IGN] raisonnement abductif [Termes IGN] raisonnement déductif [Termes IGN] raisonnement inductif Résumé : (auteur) A major focus of cartographic research can be framed within two broad trends involving geovisual analytic and critical cartographic approaches. Understated in the development both of scientific and critical approaches to the field of cartography has been the role of cartographic inference. Making inferences from maps is fundamental to the visual analytical tradition and the thinking/communication continuum. Reasoning is also fundamental to critical cartography and the development of critiques relies on inference based on “evidence” encoded or inscribed in a map or set of maps. The social construction of a map and the map’s use have a significant impact on the types of inferences that are made, but conclusions must be carefully scrutinized with respect to these inferences. This study examines the Piercean notions of abductive, deductive, and inductive inference and their application to cartographic inquiry from both scientific and critical perspectives. A study of John Snow’s famous map of a cholera outbreak in London shows the evolution of this map from an instrument of scientific inquiry to one of historical discourse. This historical discourse also shows the continuous unfolding of “Snow’s map” as a mapping practice. By understanding how logical inferences change over time as the context of a map within society changes, this study shows biases inherent within cartographic expression integral to both scientific and critical lines of inquiry. Numéro de notice : A2020-440 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart-2019-0029 Date de publication en ligne : 16/06/2020 En ligne : https://doi.org/10.3138/cart-2019-0029 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95498 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
031-2020021	SL	Revue	Centre de documentation	Revues en salle	Disponible

Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree / José Antonio Martin-Jimenez in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 146 (December 2018) . - pp 334 - 346 Titre : Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree Type de document : Article/Communication Auteurs : José Antonio Martin-Jimenez, Auteur ; Santiago Zazo, Auteur ; José Juan Arranz Justel, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 334 - 346 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] accident de la route [Termes IGN] arbre de décision [Termes IGN] cohérence géométrique [Termes IGN] données GNSS [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Espagne [Termes IGN] extraction du réseau routier [Termes IGN] indice de risque [Termes IGN] lidar mobile [Termes IGN] raisonnement [Termes IGN] sécurité routière [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] triangulation de Delaunay Résumé : (auteur) Safe roads are a necessity for any society because of the high social costs of traffic accidents. This challenge is addressed by a novel methodology that allows us to evaluate road safety from Mobile LiDAR System data, taking advantage of the road alignment due to its influence on the accident rate. Automation is obtained through an inductive reasoning process based on a decision tree that provides a potential risk assessment. To achieve this, a 3D point cloud is classified by an iterative and incremental algorithm based on a 2.5D and 3D Delaunay triangulation, which apply different algorithms sequentially. Next, an automatic extraction process of road horizontal alignment parameters is developed to obtain geometric consistency indexes, based on a joint triple stability criterion. Likewise, this work aims to provide a powerful and effective preventive and/or predictive tool for road safety inspections. The proposed methodology was implemented on three stretches of Spanish roads, each with different traffic conditions that represent the most common road types. The developed methodology was successfully validated through as-built road projects, which were considered as “ground truth.” Numéro de notice : A2018-541 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.10.004 Date de publication en ligne : 21/10/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.10.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91565 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018131	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018132	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

An Introduction to Machine Learning / Miroslav Kubat (2017)  

Public Titre : An Introduction to Machine Learning Type de document : Guide/Manuel Auteurs : Miroslav Kubat, Auteur Mention d'édition : 2ème édition Editeur : Springer International Publishing Année de publication : 2017 ISBN/ISSN/EAN : 978-3-319-63913-0 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] algorithme génétique [Termes IGN] apprentissage non-dirigé [Termes IGN] apprentissage par renforcement [Termes IGN] apprentissage profond [Termes IGN] arbre de décision [Termes IGN] classificateur [Termes IGN] classification barycentrique [Termes IGN] classification bayesienne [Termes IGN] exploration de données [Termes IGN] raisonnement inductif [Termes IGN] réseau neuronal artificiel [Termes IGN] test de performance Mots-clés libres : Bayesian classifiersboostingcomputational learning theorydecision treesgenetic algorithmslinear and polynomial classifiersnearest neighbor classifierneural networksperformance evaluationreinforcement learningstatistical learningtime-varying classes, imbalanced representationartificial intelligencemachine learningdata miningdeep learningunsupervised learning Résumé : (Auteur) [Introduction] This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and offering engaging discussions of relevant applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of “boosting,” how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms. This revised edition contains three entirely new chapters on critical topics regarding the pragmatic application of machine learning in industry. The chapters examine multi-label domains, unsupervised learning and its use in deep learning, and logical approaches to induction as well as Inductive Logic Programming. Numerous chapters have been expanded, and the presentation of the material has been enhanced. The book contains many new exercises, numerous solved examples, thought-provoking experiments, and computer assignments for independent work. Numéro de notice : 26276 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Manuel DOI : 10.1007/978-3-319-63913-0 En ligne : https://doi.org/10.1007/978-3-319-63913-0 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94915

Etude de l'usage de la couleur dans l'apprentissage des SIG en géosciences : le cas de la cartographie d'aptitude / Raffaella Balzarini in Cartes & Géomatique, n° 222 (décembre 2014)

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Panorama de l'intelligence artificielle, ses bases méthodologiques, ses développements, 1. Représentation des connaissances et formalisation des raisonnements / Pierre Marquis (2014)

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Panorama de l'intelligence artificielle, ses bases méthodologiques, ses développements, 3. L'intelligence artificielle : frontières et applications / Pierre Marquis (2014)

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Evolutionary search for understanding movement dynamics on mixed networks / William M. Spears in Geoinformatica, vol 17 n° 2 (April 2013)  

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A rough set approach to the discovery of classification rules in spatial data / Yee Leung in International journal of geographical information science IJGIS, vol 21 n° 9-10 (october 2007)  

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Evaluation in the map generalisation process / William A Mackaness (01/01/2007)

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La logique floue / Bernadette Bouchon-Meunier (2007)

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An extended cellular automaton using case-based reasoning for simulating urban development in a large complex region / X. Li in International journal of geographical information science IJGIS, vol 20 n° 10 (november 2006)  

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Evaluation of the horizontal resolution of SRTM elevation data / L. Pierce in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 11 (November 2006)  

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Conception et exploitation d'une base de métadonnées de traitements informatiques, représentation opérationnelle des connaissances d'expert / Yann Abd-El-Kader (2006)  

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