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Towards global scale segmentation with OpenStreetMap and remote sensing / Munazza Usmani in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 8 (April 2023)
[article]
Titre : Towards global scale segmentation with OpenStreetMap and remote sensing Type de document : Article/Communication Auteurs : Munazza Usmani, Auteur ; Maurizio Napolitano, Auteur ; Francesca Bovolo, Auteur Année de publication : 2023 Article en page(s) : n° 100031 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bâtiment
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données localisées des bénévoles
[Termes IGN] image à haute résolution
[Termes IGN] information sémantique
[Termes IGN] occupation du sol
[Termes IGN] OpenStreetMap
[Termes IGN] segmentation d'image
[Termes IGN] segmentation sémantique
[Termes IGN] utilisation du solRésumé : (auteur) Land Use Land Cover (LULC) segmentation is a famous application of remote sensing in an urban environment. Up-to-date and complete data are of major importance in this field. Although with some success, pixel-based segmentation remains challenging because of class variability. Due to the increasing popularity of crowd-sourcing projects, like OpenStreetMap, the need for user-generated content has also increased, providing a new prospect for LULC segmentation. We propose a deep-learning approach to segment objects in high-resolution imagery by using semantic crowdsource information. Due to satellite imagery and crowdsource database complexity, deep learning frameworks perform a significant role. This integration reduces computation and labor costs. Our methods are based on a fully convolutional neural network (CNN) that has been adapted for multi-source data processing. We discuss the use of data augmentation techniques and improvements to the training pipeline. We applied semantic (U-Net) and instance segmentation (Mask R-CNN) methods and, Mask R–CNN showed a significantly higher segmentation accuracy from both qualitative and quantitative viewpoints. The conducted methods reach 91% and 96% overall accuracy in building segmentation and 90% in road segmentation, demonstrating OSM and remote sensing complementarity and potential for city sensing applications. Numéro de notice : A2023-148 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.ophoto.2023.100031 Date de publication en ligne : 16/02/2023 En ligne : https://doi.org/10.1016/j.ophoto.2023.100031 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102807
in ISPRS Open Journal of Photogrammetry and Remote Sensing > vol 8 (April 2023) . - n° 100031[article]Semantic integration of OpenStreetMap and CityGML with formal concept analysis / Somayeh Ahmadian in Transactions in GIS, vol 26 n° 8 (December 2022)
[article]
Titre : Semantic integration of OpenStreetMap and CityGML with formal concept analysis Type de document : Article/Communication Auteurs : Somayeh Ahmadian, Auteur ; Parham Pahlavani, Auteur Année de publication : 2022 Article en page(s) : pp 3349 - 3373 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse de groupement
[Termes IGN] bâtiment
[Termes IGN] CityGML
[Termes IGN] classification par nuées dynamiques
[Termes IGN] données localisées des bénévoles
[Termes IGN] information sémantique
[Termes IGN] ontologie
[Termes IGN] OpenStreetMap
[Termes IGN] qualité des données
[Termes IGN] réseau sémantiqueRésumé : (auteur) Volunteered geographic information (VGI) provides geometric and descriptive sources of geospatial data. VGI exchange, reuse, and integration are serious challenges due to the subjective contribution process, lack of organization, and redundancy. This study aims to enhance the quality of VGI semantic data by presenting a new approach to integrating and formalizing the VGI semantic knowledge using formal concept analysis. The proposed approach is assessed using the building tags in OpenStreetMap (OSM) and CityGML. The alignment process discovers the conceptual overlap between the categories of Amenity (Others), Office, and Man-Made in Map Features (OSM) and Business and Trade, Recreation, Sport, and Industry in AbstractBuilding (CityGML). The k-means clustering of the results illustrated that class, usage/function, address, wheelchair, and website/wikidata/wikipedia are significant attributes to describe building categories. Moreover, results showed that the analysis of frequent itemsets and cluster characteristics provides significant information about custom tags in OSM's editing tools. Numéro de notice : A2022-909 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.13006 Date de publication en ligne : 02/12/2022 En ligne : https://doi.org/10.1111/tgis.13006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102347
in Transactions in GIS > vol 26 n° 8 (December 2022) . - pp 3349 - 3373[article]Improving deep learning on point cloud by maximizing mutual information across layers / Di Wang in Pattern recognition, vol 131 (November 2022)
[article]
Titre : Improving deep learning on point cloud by maximizing mutual information across layers Type de document : Article/Communication Auteurs : Di Wang, Auteur ; Lulu Tang, Auteur ; Xu Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 108892 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] entropie de Shannon
[Termes IGN] information sémantique
[Termes IGN] segmentation sémantique
[Termes IGN] semis de points
[Termes IGN] transformation géométrique
[Termes IGN] vision par ordinateur
[Termes IGN] visualisation 3DRésumé : (auteur) It is a fundamental and vital task to enhance the perception capability of the point cloud learning network in 3D machine vision applications. Most existing methods utilize feature fusion and geometric transformation to improve point cloud learning without paying enough attention to mining further intrinsic information across multiple network layers. Motivated to improve consistency between hierarchical features and strengthen the perception capability of the point cloud network, we propose exploring whether maximizing the mutual information (MI) across shallow and deep layers is beneficial to improve representation learning on point clouds. A novel design of Maximizing Mutual Information (MMI) Module is proposed, which assists the training process of the main network to capture discriminative features of the input point clouds. Specifically, the MMI-based loss function is employed to constrain the differences of semantic information in two hierarchical features extracted from the shallow and deep layers of the network. Extensive experiments show that our method is generally applicable to point cloud tasks, including classification, shape retrieval, indoor scene segmentation, 3D object detection, and completion, and illustrate the efficacy of our proposed method and its advantages over existing ones. Our source code is available at https://github.com/wendydidi/MMI.git. Numéro de notice : A2022-780 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : https://doi.org/10.1016/j.patcog.2022.108892 Date de publication en ligne : 08/07/2022 En ligne : https://doi.org/10.1016/j.patcog.2022.108892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101859
in Pattern recognition > vol 131 (November 2022) . - n° 108892[article]A relation-augmented embedded graph attention network for remote sensing object detection / Shu Tian in IEEE Transactions on geoscience and remote sensing, vol 60 n° 10 (October 2022)
[article]
Titre : A relation-augmented embedded graph attention network for remote sensing object detection Type de document : Article/Communication Auteurs : Shu Tian, Auteur ; Lihong Kang, Auteur ; Xiangwei Xing, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1000718 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] graphe
[Termes IGN] image à haute résolution
[Termes IGN] information sémantique
[Termes IGN] relation sémantique
[Termes IGN] relation spatiale
[Termes IGN] réseau neuronal de graphes
[Termes IGN] SIFT (algorithme)Résumé : (auteur) Multiclass geospatial object detection in high spatial resolution remote sensing imagery (HSRI) is still a challenging task. The main reason is that the objects in HRSI are location-variable and semantic-confusable, which results in the difficulties in differentiating the complicated spatial patterns and deriving the implicitly semantic labels among different categories of objects. In this article, we propose a relation-augmented embedded graph attention network (EGAT), which enables the full exploitation of the underlying spatial and semantic relations among objects for improving the detection performance. Specifically, we first construct two sets of spatial and semantic graphs of objects–objects for object relations modeling. Second, a Siamese architecture-based embedding spatial and semantic graph attention network is designed for relations reasoning, which is implemented by introducing the long short-term memory (LSTM) mechanism into the EGAT, for learning the relations among different categories of intraobjects and interobjects. Driven by the spatial and semantic LSTM, the EGAT-LSTM can adaptively focus on the critical information of reason graphs for spatial–semantic correlation discrimination in the embedding non-Euclidean feature space. By this way, the EGAT-LSTM can effectively capture the global and local spatial–semantic relationships of objects–objects, and then produce relations-augmented features for improving the performance of object detection. We conduct comprehensive experiments on three public datasets for multiclass geospatial object detection. Our method achieves state-of-the-art performance, which demonstrates the superiority and effectiveness of the proposed method. Numéro de notice : A2022-766 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3073269 Date de publication en ligne : 18/05/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3073269 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101788
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 10 (October 2022) . - n° 1000718[article]Deep learning method for Chinese multisource point of interest matching / Pengpeng Li in Computers, Environment and Urban Systems, vol 96 (September 2022)
[article]
Titre : Deep learning method for Chinese multisource point of interest matching Type de document : Article/Communication Auteurs : Pengpeng Li, Auteur ; Jiping Liu, Auteur ; An Luo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101821 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] appariement sémantique
[Termes IGN] apprentissage profond
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] inférence sémantique
[Termes IGN] information sémantique
[Termes IGN] point d'intérêt
[Termes IGN] représentation vectorielle
[Termes IGN] traitement du langage naturelRésumé : (auteur) Multisource point of interest (POI) matching refers to the pairing of POIs that refer to the same geographic entity in different data sources. This also constitutes the core issue in geospatial data fusion and update. The existing methods cannot effectively capture the complex semantic information from a text, and the manually defined rules largely affect matching results. This study developed a multisource POI matching method based on deep learning that transforms the POI pair matching problem into a binary classification problem. First, we used three different Chinese word segmentation methods to segment the POI text attributes and used the segmentation results to train the Word2Vec model to generate the corresponding word vector representation. Then, we used the text convolutional neural network (Text-CNN) and multilayer perceptron (MLP) to extract the POI attributes' features and generate the corresponding feature vector representation. Finally, we used the enhanced sequential inference model (ESIM) to perform local inference and inference combination on each attribute to realize the classification of POI pairs. We used the POI dataset containing Baidu Map, Tencent Map, and Gaode Map from Chengdu to train, verify, and test the model. The experimental results show that the matching precision, recall rate, and F1 score of the proposed method exceed 98% on the test set, and it is significantly better than the existing matching methods. Numéro de notice : A2022-513 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101821 Date de publication en ligne : 18/06/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101821 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101053
in Computers, Environment and Urban Systems > vol 96 (September 2022) . - n° 101821[article]Point-of-interest detection from Weibo data for map updating / Xue Yang in Transactions in GIS, vol 26 n° 6 (September 2022)PermalinkChange detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach / Joachim Gehrung in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)PermalinkSummarizing large scale 3D mesh for urban navigation / Imeen Ben Salah in Robotics and autonomous systems, vol 152 (June 2022)PermalinkMining crowdsourced trajectory and geo-tagged data for spatial-semantic road map construction / Jincai Huang in Transactions in GIS, vol 26 n° 2 (April 2022)PermalinkA method of vision aided GNSS positioning using semantic information in complex urban environment / Rui Zhai in Remote sensing, vol 14 n° 4 (February-2 2022)PermalinkQuickly locating POIs in large datasets from descriptions based on improved address matching and compact qualitative representations / Ruozhen Cheng in Transactions in GIS, vol 26 n° 1 (February 2022)PermalinkAnnotation sémantique pour la géolocalisation d'entités spatiales dans des tweets / Gaëtan Caillaut (2022)PermalinkRepresenting vector geographic information as a tensor for deep learning based map generalisation / Azelle Courtial (2022)PermalinkPermalinkPermalinkPermalinkVGI3D: an interactive and low-cost solution for 3D building modelling from street-level VGI images / Chaoquan Zhang in Journal of Geovisualization and Spatial Analysis, vol 5 n° 2 (December 2021)PermalinkUtilisation de l'apprentissage profond dans la modélisation 3D urbaine [Partie 1] / Hamza Ben Addou in Géomatique expert, n° 135 (septembre 2021)PermalinkSemantic-aware label placement for augmented reality in street view / Jianqing Jia in The Visual Computer, vol 37 n° 7 (July 2021)PermalinkSpatial knowledge acquisition with virtual semantic landmarks in mixed reality-based indoor navigation / Bing Liu in Cartography and Geographic Information Science, vol 48 n° 4 (July 2021)PermalinkSemantic signatures for large-scale visual localization / Li Weng in Multimedia tools and applications, vol 80 n° 15 (June 2021)PermalinkStop-and-move sequence expressions over semantic trajectories / Yenier Torres Izquierdo in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)PermalinkOntology-based semantic conceptualisation of historical built heritage to generate parametric structured models from point clouds / Elisabetta Colucci in Applied sciences, vol 11 n° 6 (March 2021)PermalinkPermalinkLearning to translate land-cover maps: Several multi-dimensional context-wise solutions / Luc Baudoux (2021)PermalinkPermalinkPermalinkSemantic‐based urban growth prediction / Marvin Mc Cutchan in Transactions in GIS, Vol 24 n° 6 (December 2020)PermalinkThe position of sound in audiovisual maps: an experimental study of performance in spatial memory / Nils Siepmann in Cartographica, vol 55 n° 2 (Summer 2020)PermalinkAn IEEE value loop of human-technology collaboration in geospatial information science / Liqiu Meng in Geo-spatial Information Science, vol 23 n° 1 (March 2020)PermalinkExtending Processing Toolbox for assessing the logical consistency of OpenStreetMap data / Sukhjit Singh Sehra in Transactions in GIS, Vol 24 n° 1 (February 2020)PermalinkBertin’s graphic variables and online map makers: an empirical study of maps produced by prosumers and cartographers / Natalia Ipatow in Cartographica, vol 54 n° 4 (Winter 2019)PermalinkSMSM: a similarity measure for trajectory stops and moves / Andre L. Lehmann in International journal of geographical information science IJGIS, vol 33 n° 9 (September 2019)PermalinkA natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements / Yingjie Hu in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)PermalinkIntegration of lidar data and GIS data for point cloud semantic enrichment at the point level / Harith Aljumaily in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkSemantic aware quality evaluation of 3D building models : Modeling and simulation / Oussama Ennafii (2019)PermalinkUn modèle spatiotemporel sémantique pour la modélisation de mobilités en milieu urbain / Meihan Jin in Revue internationale de géomatique, vol 28 n° 3 (juillet - septembre 2018)PermalinkL’opérateur de collage : Gestion de plusieurs points de vue dans un contexte spatial / Géraldine Del Mondo in Revue internationale de géomatique, vol 28 n° 3 (juillet - septembre 2018)PermalinkClassification of aerial photogrammetric 3D point clouds / Carlos Becker in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 5 (mai 2018)PermalinkSemantic enrichment of octree structured point clouds for multi‐story 3D pathfinding / Florian W. Fichtner in Transactions in GIS, vol 22 n° 1 (February 2018)PermalinkPermalinkPermalinkEvaluation of a spatially adaptive approach for land surface classification from digital elevation models / Maria Dekavalla in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)PermalinkCartographie et interprétation de l'environnement par drone / Martial Sanfourche in Revue Française de Photogrammétrie et de Télédétection, n° 213 - 214 (janvier - avril 2017)PermalinkD'une cartographie de flux à une cartographie du mouvement : aspects sémiologiques / Françoise Bahoken in Cartes & Géomatique, n° 229-230 (septembre 2016 - février 2017)PermalinkMultidimensional Similarity Measuring for Semantic Trajectories / Andre Salvaro Furtado in Transactions in GIS, vol 20 n° 2 (April 2016)PermalinkScalable and privacy-respectful interactive discovery of place semantics from human mobility traces / Natalia Andrienko in Information visualization, vol 15 n° 2 (April 2016)PermalinkQue représentent les références spatiales des données du Web ? un vocabulaire pour la représentation de la sémantique des XY / Abdelfettah Feliachi (2016)PermalinkPermalinkA temporal-contextual analysis of urban dynamics using location-based data / A. Yair Grinberger in International journal of geographical information science IJGIS, vol 29 n° 11 (November 2015)Permalink3D web services for visualization and data sharing in 3D cadastre / Ali Zare Zardiny in International journal of 3-D information modeling, vol 4 n° 4 (October - December 2015)PermalinkVariation du niveau d’abstraction dans le cadre de l’opérateur de zoom sémantique / Géraldine Del Mondo in Revue internationale de géomatique, vol 25 n° 2 (juin - août 2015)PermalinkFrom raw data to meaningful information: A representational approach to cadastral databases in relation to urban planning / Francecs Valls-Dalmau in Future internet, vol 6 n° 4 (December 2014)PermalinkCONSTAnT – A conceptual data model for semantic Trajectories of moving objects / Vania Bogorny in Transactions in GIS, vol 18 n° 1 (February 2014)PermalinkAmélioration de la localisation 3D de données laser terrestre à l'aide de cartes 2D ou modèles 3D / Fabrice Monnier (2014)PermalinkGeographic Information Science, 8th International Conference, GIScience 2014, Vienna Austria, September 24-26, 2014 / Matt Duckham (2014)PermalinkGeographic Object-Based Image Analysis: Towards a new paradigm / Thomas Blaschke in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkInteractive cartographic route descriptions / Padraig Corcoran in Geoinformatica, vol 18 n° 1 (January 2014)PermalinkIntelligent services for discovery of complex geospatial features from remote sensing imagery / Peng Yue in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)PermalinkAssessing the veracity of methods for extracting place semantics from Flickr tags / William A Mackaness in Transactions in GIS, vol 17 n° 4 (August 2013)PermalinkCartographic visualization of vulnerability to natural hazards / Tomasz Opach in Cartographica, vol 48 n° 2 (June 2013)PermalinkModèle pour un serveur de données géographiques. Les services web géographiques WMS et WFS / Nissrine Souissi in Revue internationale de géomatique, vol 23 n° 2 (juin - aout 2013)PermalinkVers une approche pluridisciplinaire des réseaux enterrés / Lucile Gimenez in XYZ, n° 135 (juin - août 2013)Permalink2D arrangement-based hierarchical spatial partitioning: an application to pedestrian network generation / Murat Yirci (2013)PermalinkQuality evaluation of 3D city building models with automatic error diagnosis / Jean-Christophe Michelin (2013)PermalinkWhen script engravings reveal a semantic link between the conceptual and the spatial dimensions of a monument: The case of the tomb of Emperor Qianlong / Livio de Luca (2013)PermalinkMathematical morphology-based generalization of complex 3D building models incorporating semantic relationships / J. Zhao in ISPRS Journal of photogrammetry and remote sensing, vol 68 (March 2012)PermalinkPermalinkHow many 3D city models are there? A typological try / M. Jahnke in Cartographic journal (the), vol 48 n° 2 (May 2011)PermalinkA semantic-rich multi-scale information model for topography / Jantien E. Stoter in International journal of geographical information science IJGIS, vol 25 n° 4-5 (May 2011)PermalinkLa valeur des données géographiques / Christophe Terrier in Espace géographique, vol 40 n° 2 (avril - juin 2011)PermalinkOntologies of geographic information / Helen Couclelis in International journal of geographical information science IJGIS, vol 24 n°11-12 (december 2010)PermalinkInsertion of 3-D-primitives in mesh-based representations: Towards compact models preserving the details / Florent Lafarge in IEEE Transactions on image processing, vol 19 n° 7 (July 2010)PermalinkPermalinkPermalinkMesure de la distance sémantique entre parties potentiellement communes à deux taxonomies / Ammar Mechouche (2010)PermalinkA semantic registry using a feature type catalogue instead of ontologies to support spatial data infrastructures / K. Stock in International journal of geographical information science IJGIS, vol 24 n°1-2 (january 2010)PermalinkSemantics-based 3D dynamic hierarchical house property model / Q. Zhu in International journal of geographical information science IJGIS, vol 24 n°1-2 (january 2010)PermalinkA framework for the generalization of 3D city models / R. Guercke in Bulletin des sciences géographiques, n° 23 (juin 2009)PermalinkLa sémantique de scènes 3D : une approche sémantique pour l'adaptation et la réutilisation de scènes 3D / I. Bilasco in Le monde des cartes, n° 198 (décembre 2008)PermalinkRelations among map objects in cartographic generalization / Stefan Steiniger in Cartography and Geographic Information Science, vol 34 n° 3 (July 2007)PermalinkContextualization of geospatial database semantics for Human-GIS Interaction / G. Cai in Geoinformatica, vol 11 n° 2 (June - August 2007)PermalinkPattern matching for heterogeneous geodata sources using attributed relational graph and probabilistic relaxation / S. Yi in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 6 (June 2007)PermalinkGestion des liens entre la représentation spatiale et les informations alphanumériques associées à un objet géographique : Généralisation aux représentations composites et non simplement connexes / J. Lecoq in Revue internationale de géomatique, vol 17 n° 1 (mars – mai 2007)PermalinkApport automatisé de sémantique lors de manipulations de documents géographiques / Michel Mainguenaud in Revue internationale de géomatique, vol 16 n° 2 (juin – août 2006)PermalinkEnrichissement de bases de connaissances par l'annotation sémantique : plate-forme web sémantique avec des outils linguistiques pour des activités de veille et d'édition / F. Amardeihl in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 11 n° 2 (mars - avril 2006)PermalinkA framework to enhance semantic flexibility for analysis of distributed phenomena / J Mcintosh in International journal of geographical information science IJGIS, vol 19 n° 10 (november 2005)Permalink