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A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data / Luis Vilches-Blazquez in Transactions in GIS, vol 23 n° 1 (February 2019)
[article]
Titre : A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data Type de document : Article/Communication Auteurs : Luis Vilches-Blazquez, Auteur ; Jhonny Saavedra, Auteur Année de publication : 2019 Article en page(s) : pp 22 - 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] biodiversité
[Termes IGN] cadre conceptuel
[Termes IGN] données localisées
[Termes IGN] données multisources
[Termes IGN] GML
[Termes IGN] interopérabilité
[Termes IGN] partage de données localisées
[Termes IGN] RDF
[Termes IGN] regroupement de données
[Termes IGN] web des données
[Termes IGN] Web Feature Service
[Termes IGN] web sémantiqueRésumé : (auteur) Diverse studies have shown that about 80% of all available data are related to a spatial location. Most of these geospatial data are available as structured and semi‐structured datasets, and often use distinct data models, are encoded using ad‐hoc vocabularies, and sometimes are being published in non‐standard formats. Hence, these data are isolated within silos and cannot be shared and integrated across organizations and communities. Spatial Data Infrastructures (SDIs) have emerged and contributed to significantly enhance data discovery and accessibility based on OGC (Open Geospatial Consortium) Web services. However, finding, accessing, and using data disseminated through SDIs are still difficult for non‐expert users. Overcoming the current geospatial data challenges involves adopting the best practices to expose, share, and integrate data on the Web, that is, Linked Data. In this article, we have developed a framework for generating, enriching, and exploiting geospatial Linked Data from multiple and heterogeneous geospatial data sources. This proposal allows connecting two interoperability universes (SDIs, more specifically Web Feature Services, WFS, and Semantic Web technologies), which is evaluated through a study case in the (geo)biodiversity domain. Numéro de notice : A2019-089 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12496 Date de publication en ligne : 28/11/2018 En ligne : https://doi.org/10.1111/tgis.12496 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92236
in Transactions in GIS > vol 23 n° 1 (February 2019) . - pp 22 - 47[article]
Titre : Process modelling and simulation Type de document : Monographie Auteurs : Cesar De Prada, Éditeur scientifique ; Costas Pantelides, Éditeur scientifique ; Jose Luis Pitarch, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 298 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 9783039214556 9783039214563 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Informatique
[Termes IGN] estimation statistique
[Termes IGN] modèle conceptuel de données
[Termes IGN] modèle de simulation
[Termes IGN] modèle géométrique
[Termes IGN] modèle mathématique
[Termes IGN] modélisation
[Termes IGN] optimisation (mathématiques)Résumé : (éditeur) Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications. Note de contenu : 1- Data-mining for processes in chemistry, materials, and engineering
2- Incremental parameter estimation under rank-deficient measurement conditions
3- Sequential parameter estimation for mammalian cell model based on In Silico design
of experiments
4- Toward a comprehensive and efficient robust optimization framework for (Bio)chemical
processes
5- A systematic grey-box modeling methodology via data reconciliation and SOS constrained regression
6- Toward a distinct and quantitative validation method for predictive process extracts
7- GEKKO optimization suite
8- Modelling condensation and simulation for wheat germ drying in fluidized bed dryer
9- Model development and validation of fluid bed wet granulation with dry binder addition using a population balance model methodology
10- Modeling on-site combined heat and power systems coupled to main process operation
11- Mathematical modelling forecast on the idling transient characteristic of reactor
coolant pump
12- Numerical simulation of water absorption and swelling in dehulled barley grains during canned porridge cooking
13- Wave characteristics of coagulation bath in dry-jet wet-spinning process for polyacrylonitrile fiber production using computational fluid dynamics
14- Evaluation of the influences of scrap melting and dissolution during dynamic Linz–Donawitz (LD) converter modellingNuméro de notice : 28502 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Monographie DOI : 10.3390/books978-3-03921-456-3 En ligne : https://doi.org/10.3390/books978-3-03921-456-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97001 Towards visual urban scene understanding for autonomous vehicle path tracking using GPS positioning data / Citlalli Gamez Serna (2019)
Titre : Towards visual urban scene understanding for autonomous vehicle path tracking using GPS positioning data Type de document : Thèse/HDR Auteurs : Citlalli Gamez Serna, Auteur ; Yassine Ruichek, Directeur de thèse Editeur : Dijon : Université Bourgogne Franche-Comté UBFC Année de publication : 2019 Importance : 178 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 : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] compréhension de l'image
[Termes IGN] instance
[Termes IGN] milieu urbain
[Termes IGN] navigation autonome
[Termes IGN] récepteur GPS
[Termes IGN] scène urbaine
[Termes IGN] segmentation sémantique
[Termes IGN] signalisation routière
[Termes IGN] système de transport intelligent
[Termes IGN] trajectoire (véhicule non spatial)
[Termes IGN] véhicule sans pilote
[Termes IGN] vision par ordinateur
[Termes IGN] vision stéréoscopique
[Termes IGN] vitesseMots-clés libres : suivi d'itinéraire Index. décimale : THESE Thèses et HDR Résumé : (auteur) This PhD thesis focuses on developing a path tracking approach based on visual perception and localization in urban environments. The proposed approach comprises two systems. The first one concerns environment perception. This task is carried out using deep learning techniques to automatically extract 2D visual features and use them to learn in order to distinguish the different objects in the driving scenarios. Three deep learning techniques are adopted: semantic segmentation to assign each image pixel to a class, instance segmentation to identify separated instances of the same class and, image classification to further recognize the specific labels of the instances. Here our system segments 15 object classes and performs traffic sign recognition. The second system refers to path tracking. In order to follow a path, the equipped vehicle first travels and records the route with a stereo vision system and a GPS receiver (learning step). The proposed system analyses off-line the GPS path and identifies exactly the locations of dangerous (sharp) curves and speed limits. Later after the vehicle is able to localize itself, the vehicle control module together with our speed negotiation algorithm, takes into account the information extracted and computes the ideal speed to execute. Through experimental results of both systems, we prove that, the first one is capable to detect and recognize precisely objects of interest in urban scenarios, while the path tracking one reduces significantly the lateral errors between the learned and traveled path. We argue that the fusion of both systems will ameliorate the tracking approach for preventing accidents or implementing autonomous driving. Note de contenu : I- Context and problems
1- Introduction
II- Contribution
2- Proposed datasets
3- Traffic sign classification
4- Visual perception system for urban environments
5- Dynamic speed adaptation system for path tracking based on curvature
information and speed limits
III- Conclusions and future works
6- Conclusions and future worksNuméro de notice : 25967 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique : UBFC : 2019 Organisme de stage : CIAD Dijon nature-HAL : Thèse DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-02160966/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96587 GIS approach to publishing commonfacilities plans of land consolidation in the Czech Republic / Arnošt Müller in Geodetski vestnik, vol 62 n° 4 (December 2018 - February 2019)
[article]
Titre : GIS approach to publishing commonfacilities plans of land consolidation in the Czech Republic Type de document : Article/Communication Auteurs : Arnošt Müller, Auteur Année de publication : 2018 Article en page(s) : pp 641 - 656 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] base de données foncières
[Termes IGN] base de données localisées
[Termes IGN] cadastre étranger
[Termes IGN] changement climatique
[Termes IGN] données environnementales
[Termes IGN] données hydrographiques
[Termes IGN] érosion
[Termes IGN] modèle orienté objet
[Termes IGN] normalisation
[Termes IGN] paysage agricole
[Termes IGN] remembrement agricole
[Termes IGN] République TchèqueRésumé : (auteur) This paper introduces the process of land consolidation and current use of geographic information systems (GIS) in the Czech Republic. Contemporary land consolidation in the Central European region, unlike Western Europe, has been implemented relatively recently, hence there is no contingency or previous experience to build upon. This brings about an opportunity for a modern design of GIS‐based land consolidation. Although the design of land consolidation projects in the Czech Republic is mainly conducted in CAD software, this paper focuses on the utilisation of GIS and stresses the importance of standardisation of land consolidation data. Standardisation allows automatic processing of data as well as effortless publishing. The author proposes a new object‐oriented data model of the landscape plan (Common Facilities Plan), which allows for the storing of such plans in a central spatial database and adding attribute information to each object, thus providing analysis of the data in a GIS. The data model alongside data standardisation lays the groundwork for the architectural proposal of a new GIS (geoportal) of Common Facilities Plans. Numéro de notice : A2019-017 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.15292/geodetski-vestnik.2018.04.641-656 Date de publication en ligne : 03/12/2018 En ligne : https://doi.org/10.15292/geodetski-vestnik.2018.04.641-656 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91631
in Geodetski vestnik > vol 62 n° 4 (December 2018 - February 2019) . - pp 641 - 656[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 139-2018041 RAB Revue Centre de documentation En réserve L003 Disponible Scene classification based on multiscale convolutional neural network / Yanfei Liu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Scene classification based on multiscale convolutional neural network Type de document : Article/Communication Auteurs : Yanfei Liu, Auteur ; Yanfei Zhong, Auteur ; Qianqing Qin, Auteur Année de publication : 2018 Article en page(s) : pp 7109 - 7121 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à haute résolution
[Termes IGN] image aérienne
[Termes IGN] image multidimensionnelle
[Termes IGN] image satellite
[Termes IGN] mesure de similitude
[Termes IGN] modèle orienté objetRésumé : (auteur) With the large amount of high-spatial resolution images now available, scene classification aimed at obtaining high-level semantic concepts has drawn great attention. The convolutional neural networks (CNNs), which are typical deep learning methods, have widely been studied to automatically learn features for the images for scene classification. However, scene classification based on CNNs is still difficult due to the scale variation of the objects in remote sensing imagery. In this paper, a multiscale CNN (MCNN) framework is proposed to solve the problem. In MCNN, a network structure containing dual branches of a fixed-scale net (F-net) and a varied-scale net (V-net) is constructed and the parameters are shared by the F-net and V-net. The images and their rescaled images are fed into the F-net and V-net, respectively, allowing us to simultaneously train the shared network weights on multiscale images. Furthermore, to ensure that the features extracted from MCNN are scale invariant, a similarity measure layer is added to MCNN, which forces the two feature vectors extracted from the image and its corresponding rescaled image to be as close as possible in the training phase. To demonstrate the effectiveness of the proposed method, we compared the results obtained using three widely used remote sensing data sets: the UC Merced data set, the aerial image data set, and the google data set of SIRI-WHU. The results confirm that the proposed method performs significantly better than the other state-of-the-art scene classification methods. Numéro de notice : A2018-556 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2848473 Date de publication en ligne : 26/07/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2848473 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91660
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 7109 - 7121[article]Ontologies pour représenter l’évolution des découpages territoriaux statistiques / Camille Bernard in Revue internationale de géomatique, vol 28 n° 4 (octobre - décembre 2018)PermalinkLabel propagation with ensemble of pairwise geometric relations : towards robust large-scale retrieval of object instances / Xiaomeng Wu in International journal of computer vision, vol 126 n° 7 (July 2018)PermalinkA spatio-temporal scenario model for emergency decision / Cheng Liu in Geoinformatica, vol 22 n° 2 (April 2018)PermalinkAnalyse de l'incertitude et de la précision thématique de classifications GEOBIA d'une image WorldView-2 / François Messner in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)PermalinkLabelling hierarchy for street maps using centrality measures / Wasim Shoman in Cartographic journal (the), vol 55 n° 1 (February 2018)PermalinkPermalinkHarmonisation de données géographiques hétérogènes décrivant le réseau d’assainissement francilien / Laurie Nino (2018)PermalinkA hydrological sensor web ontology based on the SSN ontology: A case study for a flood / Chao Wang in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)PermalinkResearches about the living condition in Ulaanbaatar with mapping developments based on a participatory approach / Paul Roux (2018)PermalinkPermalinkQuantifying the sources of epistemic uncertainty in model predictions of insect disturbances in an uncertain climate / David R. Gray in Annals of Forest Science, vol 74 n° 3 (September 2017)PermalinkExtrapolated georeferencing of high-resolution satellite imagery based on the strip constraint / Jinshan Cao in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 7 (July 2017)PermalinkKnowledge-based data enrichment for HBIM: Exploring high-quality models using the semantic-web / Ramona Quattrini in Journal of Cultural Heritage, vol 28 (November–December 2017)PermalinkGeometric features and their relevance for 3D point cloud classification / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-1/W1 (May 2017)PermalinkAerial lidar point cloud voxelization with its 3D ground filtering application / Liying Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 2 (February 2017)PermalinkDelineation of groundwater potential zones using remote sensing and GIS-based data-driven models / Samira Ghorbani Nejad in Geocarto international, vol 32 n° 2 (February 2017)PermalinkPermalinkBibframe, un nouveau modèle de données pour les bibliothèques / Reinhold Heuvelmann in Arabesques, n° 83 (juillet - septembre 2016)PermalinkIntegrating social network data into GISystems / Clio Andris in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)PermalinkPermalink