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Real-time mapping of natural disasters using citizen update streams / Iranga Subasinghe in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)
[article]
Titre : Real-time mapping of natural disasters using citizen update streams Type de document : Article/Communication Auteurs : Iranga Subasinghe, Auteur ; Silvia Nittel, Auteur ; Michael Cressey, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 393 - 421 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] approche participative
[Termes IGN] cartographie collaborative
[Termes IGN] catastrophe naturelle
[Termes IGN] classification par réseau neuronal
[Termes IGN] diagramme de Voronoï
[Termes IGN] données localisées des bénévoles
[Termes IGN] effondrement de terrain
[Termes IGN] incendie
[Termes IGN] inondation
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] système multi-agents
[Termes IGN] tempête
[Termes IGN] temps réel
[Termes IGN] ville intelligenteRésumé : (auteur) Natural disasters such as flooding, wildfires, and mudslides are rare events, but they affect citizens at unpredictable times and the impact on human life can be significant. Citizens located close to events can provide detailed, real-time data streams capturing their event response. Instead of visualizing individual updates, an integrated spatiotemporal map yields ‘big picture’ event information. We investigate the question of whether information from affected citizens is sufficient to generate a map of an unfolding natural disaster. We built the Citizen Disaster Reaction Multi-Agent Simulation (CDR-MAS), a multi-agent system that simulates the reaction of citizens to a natural disaster in an urban region. We proposed an rkNN classification algorithm to aggregate the update streams into a series of colored Voronoi event maps. We simulated the 2018 Montecito Creek mudslide and customized the CDR-MAS with the local environment to systematically generate stream data sets. Our experimental evaluation showed that event mapping based on citizen update streams is significantly influenced by the amount of citizen participation and movement. Compared with a baseline of 100% participation, with 40% citizen participation, the event region was predicted with 40% accuracy, showing that citizen update streams can provide timely information in a smart city. Numéro de notice : A2020-031 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1639185 Date de publication en ligne : 15/07/2019 En ligne : https://doi.org/10.1080/13658816.2019.1639185 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94486
in International journal of geographical information science IJGIS > vol 34 n° 2 (February 2020) . - pp 393 - 421[article]
[article]
Titre : A survey on graph kernels Type de document : Article/Communication Auteurs : Nils M. Kriege, Auteur ; Fredrik D. Johansson, Auteur ; Christopher Morris, Auteur Année de publication : 2020 Article en page(s) : n° 5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] apprentissage profond
[Termes IGN] graphe
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] réseau neuronal de graphesRésumé : (auteur) Graph kernels have become an established and widely-used technique for solving classification tasks on graphs. This survey gives a comprehensive overview of techniques for kernel-based graph classification developed in the past 15 years. We describe and categorize graph kernels based on properties inherent to their design, such as the nature of their extracted graph features, their method of computation and their applicability to problems in practice. In an extensive experimental evaluation, we study the classification accuracy of a large suite of graph kernels on established benchmarks as well as new datasets. We compare the performance of popular kernels with several baseline methods and study the effect of applying a Gaussian RBF kernel to the metric induced by a graph kernel. In doing so, we find that simple baselines become competitive after this transformation on some datasets. Moreover, we study the extent to which existing graph kernels agree in their predictions (and prediction errors) and obtain a data-driven categorization of kernels as result. Finally, based on our experimental results, we derive a practitioner’s guide to kernel-based graph classification. Numéro de notice : A2020-858 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s41109-019-0195-3 Date de publication en ligne : 14/01/2020 En ligne : https://doi.org/10.1007/s41109-019-0195-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98905
in Applied network science > vol 5 (2020) . - n° 5[article]
Titre : Fast computation of distances in a tree Titre original : Calcul rapide de distances dans un arbre Type de document : Article/Communication Auteurs : Marc Pierrot-Deseilligny , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2020 Importance : 8 p. Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Algorithmique
[Termes IGN] arbre (mathématique)
[Termes IGN] distance (mathématique)Résumé : (Auteur) Computation of distances between two submits of a tree is an operation that occurs in some pattern recognition problem. When this operation has to be done thousands of times on millions of trees, the linear standard algorithms in OpN q for each pair may be a bottleneck to the global computation. This note present recursive spliting method with a complexity of OplogpN qq on each pair in worst case, and Op1q in average on all pair, once a pre-computation OpN logpN qq has been done on the whole tree. A commented C++ implementation is published as a companion to this note. Numéro de notice : P2020-004 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Preprint nature-HAL : Préprint DOI : sans Date de publication en ligne : 05/05/2020 En ligne : https://hal.science/hal-02563859 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95036 Documents numériques
en open access
Fast computation of distances in a tree - pdf preprintAdobe Acrobat PDF Geographies of maritime transport, Ch. 4. Geography versus topology in the evolution of the global container shipping network (1977-2016) / César Ducruet (2020)
Titre de série : Geographies of maritime transport, Ch. 4 Titre : Geography versus topology in the evolution of the global container shipping network (1977-2016) Type de document : Chapitre/Contribution Auteurs : César Ducruet, Auteur ; Justin Berli , Auteur ; Mattia Bunel , Auteur Editeur : Camberley [Royaume Uni] : Edward Elgar Publishing Année de publication : 2020 Projets : 1-Pas de projet / Importance : pp 49 - 70 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données spatiotemporelles
[Termes IGN] navire
[Termes IGN] système d'information géographique
[Termes IGN] théorie des graphes
[Termes IGN] transport maritimeRésumé : (Auteur) The dynamical properties of so-called spatial and complex networks are often overlooked in graph theory and network science in general. Container shipping provides a rare example of a global transport network that went through tremendous technological and geographic changes in the last decades or so. This chapter proposes for the first time an empirical analysis of no less than 40 years of inter-port vessel movement data (1977-2016) to describe the evolving properties of the global container shipping network. Main results confirm a number of stylized facts such as the growing size, connectivity, and centralization of this network due to several factors such as economies of scale in liner shipping and the rationalization of related maritime services, the emergence of hub ports, etc. We also provide a new cartography of how had the global container shipping network been geographically distributed over time, thereby highlighting major shifts in terms of port hierarchies and main corridors. We believe that this chapter will contribute to a better understanding of the complex linkages between network structure, technological change, and spatial change, opening the way for new research paths on maritime transport research and network science in general when focusing on evolutionary dynamics. Numéro de notice : H2020-002 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Chapître / contribution nature-HAL : ChOuvrScient DOI : 10.4337/9781788976640.00008 Date de publication en ligne : 16/04/2020 En ligne : https://doi.org/10.4337/9781788976640.00008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95084 Documents numériques
en open access
Geography vs. topology... - pdf auteurAdobe Acrobat PDF Image processing applications in object detection and graph matching: from Matlab development to GPU framework / Beibei Cui (2020)
Titre : Image processing applications in object detection and graph matching: from Matlab development to GPU framework Type de document : Thèse/HDR Auteurs : Beibei Cui, Auteur ; Jean-Charles Créput, Directeur de thèse Editeur : Dijon : Université Bourgogne Franche-Comté UBFC Année de publication : 2020 Importance : 137 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de Doctorat de l'Université Bourgogne Franche-Comté préparée à l'Université de Technologie de Belfort-Montbéliard, InformatiqueLangues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement de graphes
[Termes IGN] détection d'objet
[Termes IGN] entropie
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] graphe planaire
[Termes IGN] Matlab
[Termes IGN] ondelette
[Termes IGN] processeur graphique
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconnaissance de formesIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Automatically finding correspondences between object features in images is of main interest for several applications, as object detection and tracking, flow velocity estimation, identification, registration, and many derived tasks. In this thesis, we address feature correspondence within the general framework of graph matching optimization and with the principal aim to contribute, at a final step, to the design of new and parallel algorithms and their implementation on GPU (Graphics Processing Unit) systems. Graph matching problems can have many declinations, depending on the assumptions of the application at hand. We observed a gap between applications based on local cost objective functions, and those applications with higher-order cost functions, that evaluate similarity between edges of the graphs, or hyperedges when considering hypergraphs. The former class provides convolution-based algorithms already having parallel GPU implementations. Whereas, the latter class puts the emphasis on geometric inter-feature relationships, transforming the correspondence problem to a purely geometric problem stated in a high dimensional space, generally modeled as an integer quadratic programming, for which we did not find GPU implementations available yet.Two complementary approaches were adopted in order to contribute to addressing higher-order geometric graph matching on GPU. Firstly, we study different declinations of feature correspondence problems by the use of the Matlab platform, in order to reuse and provide state-of-the-art solution methods, as well as experimental protocols and input data necessary for a GPU platform with evaluation and comparison tools against existing sequential algorithms, most of the time developed in Matlab framework. Then, the first part of this work concerns three contributions, respectively, to background and frame difference application, to feature extraction problem from images for local correspondences, and to the general graph matching problem, all based on the combination of methods derived from Matlab environment. Secondly, and based on the results of Matlab developments, we propose a new GPU framework written in CUDA C++ specifically dedicated to geometric graph matching but providing new parallel algorithms, with lower computational complexity, as the self-organizing map in the plane, derived parallel clustering algorithms, and distributed local search method. These parallel algorithms are then evaluated and compared to the state-of-the-art methods available for graph matching and following the same experimental protocol. This GPU platform constitutes our final and main proposal to contribute to bridging the gap between GPU development and higher-order graph matching. Note de contenu : 1- Introduction
2- Background
3- Background subtraction and frame difference for multi-object detection
4- Using Marr-wavelets and entropy/response to automatic feature detection
5- Affinity-preserving fixed point APRIP in Matlab framework for graph matching
6- Planar graph matching in GPU
7- Conclusion and future workNuméro de notice : 28328 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique : UBFC : 2020 Organisme de stage : CIAD Dijon DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-02902973/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98402 PermalinkPermalinkSimplicial complexes reconstruction and generalisation of 3d lidar data in urban scenes / Stéphane Guinard (2020)PermalinkAn indoor navigation model and its network extraction / Filippo Mortari in Applied geomatics, Vol 11 n° 4 (December 2019)PermalinkA space-time varying graph for modelling places and events in a network / Ikechukwu Maduako in International journal of geographical information science IJGIS, vol 33 n° 10 (October 2019)PermalinkModelling of buildings from aerial LiDAR point clouds using TINs and label maps / Minglei Li in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)PermalinkAnalysis of collaboration networks in OpenStreetMap through weighted social multigraph mining / Quy Thy Truong in International journal of geographical information science IJGIS, vol 33 n° 7 - 8 (July - August 2019)PermalinkReliable image matching via photometric and geometric constraints structured by Delaunay triangulation / San Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 153 (July 2019)PermalinkComputing and querying strict, approximate, and metrically refined topological relations in linked geographic data / Blake Regalia in Transactions in GIS, vol 23 n° 3 (June 2019)PermalinkDeeply integrating linked data with geographic information systems / Gengchen Mai in Transactions in GIS, vol 23 n° 3 (June 2019)Permalink