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Attention-based vandalism detection in OpenStreetMap / Nicolas Tempelmeier (2022)  

Public Titre : Attention-based vandalism detection in OpenStreetMap Type de document : Article/Communication Auteurs : Nicolas Tempelmeier, Auteur ; Elena Demidova, Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2022 Conférence : WWW 2022, ACM Web Conference 2022 25/04/2022 29/04/2022 Lyon online France Proceedings ACM Importance : pp 643 - 651 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] attention (apprentissage automatique) [Termes IGN] détection d'anomalie [Termes IGN] fiabilité des données [Termes IGN] historique des données [Termes IGN] OpenStreetMap Mots-clés libres : vandalisme Résumé : (auteur) OpenStreetMap (OSM), a collaborative, crowdsourced Web map, is a unique source of openly available worldwide map data, increasingly adopted in Web applications. Vandalism detection is a critical task to support trust and maintain OSM transparency. This task is remarkably challenging due to the large scale of the dataset, the sheer number of contributors, various vandalism forms, and the lack of annotated data. This paper presents Ovid - a novel attention-based method for vandalism detection in OSM. Ovid relies on a novel neural architecture that adopts a multi-head attention mechanism to summarize information indicating vandalism from OSM changesets effectively. To facilitate automated vandalism detection, we introduce a set of original features that capture changeset, user, and edit information. Furthermore, we extract a dataset of real-world vandalism incidents from the OSM edit history for the first time and provide this dataset as open data. Our evaluation conducted on real-world vandalism data demonstrates the effectiveness of Ovid. Numéro de notice : C2022-008 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Communication DOI : 10.1145/3485447.3512224 Date de publication en ligne : 25/04/2022 En ligne : https://doi.org/10.1145/3485447.3512224 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100493

How to spatialize geographical iconographic heritage / Emile Blettery (2021)    

Public contenu dans SUMAC'21: Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2021)   Titre : How to spatialize geographical iconographic heritage Type de document : Article/Communication Auteurs : Emile Blettery , Auteur ; Nelson Fernandes, Auteur ; Valérie Gouet-Brunet , Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2021 Projets : Alegoria / Gouet-Brunet, Valérie Conférence : SUMAC 2021, 3rd workshop on Structuring and Understanding of Multimedia heritAge Contents 20/10/2021 24/10/2021 Chengdu Chine Proceedings ACM Importance : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] base de données d'images [Termes IGN] estimation de pose [Termes IGN] géolocalisation [Termes IGN] géoréférencement indirect [Termes IGN] image ancienne [Termes IGN] image numérisée [Termes IGN] patrimoine culturel [Termes IGN] photographie aérienne oblique [Termes IGN] photographie terrestre [Termes IGN] recherche d'image basée sur le contenu Résumé : (auteur) This article is dedicated to the spatialization of image contents, with a focus on geographical iconographic heritage, i.e. digitized or born-digital image collections, acquired at variable temporal periods and showing the territory and its human-made and natural visual landmarks. We present a panorama of the current solutions (manual, semi-automatic and fully automatic alternatives) that exist to spatialize a visual content, with respect to the data available and the level of spatialization targeted. In particular, we highlight the characteristics of the approaches dedicated to geographical iconographic heritage, and in some cases, we present tests and practical feedbacks that we had the opportunity to conduct for old photographic contents in oblique aerial and terrestrial imagery. Numéro de notice : C2021-035 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1145/3475720.3484444 En ligne : https://doi.org/10.1145/3475720.3484444 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99054

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Learning embeddings for cross-time geographic areas represented as graphs / Margarita Khokhlova (2021)  

Public Titre : Learning embeddings for cross-time geographic areas represented as graphs Type de document : Article/Communication Auteurs : Margarita Khokhlova, Auteur ; Nathalie Abadie , Auteur ; Valérie Gouet-Brunet , Auteur ; Liming Chen, Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2021 Projets : Alegoria / Gouet-Brunet, Valérie Conférence : SAC 2021, 36th Annual ACM Symposium on Applied Computing 22/03/2021 26/03/2021 en ligne Chine Proceedings ACM Importance : pp 559 - 568 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] arête [Termes IGN] classification par réseau neuronal [Termes IGN] entité géographique [Termes IGN] graphe flou [Termes IGN] image aérienne à axe vertical [Termes IGN] noeud [Termes IGN] relation spatiale [Termes IGN] représentation graphique [Termes IGN] réseau neuronal de graphes Résumé : (auteur) Geographic entities from the vertical aerial images can be viewed as discrete objects and represented as nodes in a graph, linked to each other by edges capturing their spatial relationships. Over time, the natural and man made landscape may evolve and thus also their graph representations. This paper addresses the challenging problem of the retrieval and fuzzy matching of graphs to localize near-identical geographical areas across time. Several use-case scenarios are proposed for the end-to-end learning of a graph embedding using Graph Neural Networks (GNN), along with an effective baseline without learning. The results demonstrate the efficiency of our approach, that enables efficient similarity reasoning for novel hand-engineered cross-time graph data. Code and data processing scripts are available online. Numéro de notice : C2021-002 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1145/3412841.3441936 En ligne : https://doi.org/10.1145/3412841.3441936 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97583

SUMAC'21: Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2021)  

Public Titre : SUMAC'21: Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge Contents Type de document : Actes de congrès Auteurs : Valérie Gouet-Brunet , Éditeur scientifique ; Margarita Khokhlova, Éditeur scientifique ; Ronak Kosti, Éditeur scientifique ; Li Weng , Éditeur scientifique Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2021 Conférence : SUMAC 2021, 3rd workshop on Structuring and Understanding of Multimedia heritAge Contents 20/10/2021 24/10/2021 Chengdu Chine Proceedings ACM Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] exploration d'images [Termes IGN] image numérique [Termes IGN] image numérisée [Termes IGN] patrimoine culturel [Termes IGN] recherche d'image basée sur le contenu Numéro de notice : 13912 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Actes nature-HAL : DirectOuvrColl/Actes DOI : 10.1145/3475720 En ligne : https://doi.org/10.1145/3475720 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99053

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• How to spatialize geographical iconographic heritage / Emile Blettery (2021)    

SUMAC'20 : Proceedings of the 2nd Workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2020)  

Public Titre : SUMAC'20 : Proceedings of the 2nd Workshop on Structuring and Understanding of Multimedia heritAge Contents Type de document : Actes de congrès Auteurs : Valérie Gouet-Brunet , Auteur ; Margarita Khokhlova, Auteur ; Ronak Kosti, Auteur ; Liming Chen, Auteur ; Xu-Chen Yin, Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2020 Projets : Alegoria / Gouet-Brunet, Valérie Conférence : SUMAC 2020, 2nd workshop on Structuring and Understanding of Multimedia heritAge Contents 12/10/2020 12/10/2020 en ligne Etats-Unis Proceedings ACM ISBN/ISSN/EAN : 978-1-4503-8155-0 Langues : Anglais (eng) Descripteur : [Termes IGN] conservation du patrimoine [Termes IGN] descripteur [Termes IGN] données massives [Termes IGN] multimedia [Termes IGN] numérisation de photographie [Termes IGN] recherche d'image basée sur le contenu Résumé : (auteur) It is our great pleasure to welcome you to SUMAC 2020, the 2nd edition of the ACM workshop on Structuring and Understanding of Multimedia heritAge Contents. The digitization of large quantities of analogue data and the massive production of born-digital documents for many years now provide us with large volumes of varied multimedia data (images, maps, text, video, multi-sensor data, etc.), an important feature of which is that they are cross-domain. "Cross-domain" reflects the fact that these data may have been acquired in very different conditions: different acquisition systems, times and points of view (e.g. a 1962 postcard from the Arc de Triomphe vs. a recent street-view acquisition by mobile mapping of the same monument). These data represent an extremely rich heritage that can be exploited in a wide variety of fields, from SSH to land use and territorial policies, including smart city, urban planning, tourism, creative media and entertainment. In terms of research in computer science, they address challenging problems related to the diversity and volume of the media across time, the variety of content descriptors (potentially including the time dimension), the veracity of the data, and the different user needs with respect to engaging with this rich material and the extraction of value out of the data. These challenges are reflected in research topics such as multimodal and mixed media search, automatic content analysis, multimedia linking and recommendation, and big data analysis and visualization, where scientific bottlenecks may be exacerbated by the time dimension, which also provides topics of interest such as multimodal time series analysis. Numéro de notice : 17631 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Actes nature-HAL : DirectOuvrColl/Actes DOI : 10.1145/3423323 En ligne : https://dl.acm.org/doi/proceedings/10.1145/3423323 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97086

Challenging deep image descriptors for retrieval in heterogeneous iconographic collections / Dimitri Gominski (2019)  

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SUMAC 2019, 1st workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2019)  

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SUMAC 2019: The 1st workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2019)  

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Assessing the planimetric accuracy of Paris atlases from the late 18th and 19th centuries / Bertrand Duménieu (2018)    

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An adaptive approach for interlinking georeferenced data / Abdelfettah Feliachi (2017)  

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Continuously generalizing buildings to built-up areas by aggregating and growing / Dongliang Peng (2017)  

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Evaluation of NER systems for the recognition of place mentions in French thematic corpora / Carmen Brando (2016)  

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Progressive streaming and massive rendering of 3D city models on web-based virtual globe / Quoc-Dinh Nguyen (2016)  

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Realtime projective multi-texturing of pointclouds and meshes for a realistic street-view web navigation / Alexandre Devaux (2016)    

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A multi-layer markup language for geospatial semantic annotations / Ludovic Moncla (2015)  

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