Descripteur
Termes IGN > informatique > intelligence artificielle > apprentissage automatique > apprentissage dirigé
apprentissage dirigéSynonyme(s)apprentissage superviséVoir aussi |
Documents disponibles dans cette catégorie (94)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Reconstruction of itineraries from annotated text with an informed spanning tree algorithm / Ludovic Moncla in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)
[article]
Titre : Reconstruction of itineraries from annotated text with an informed spanning tree algorithm Type de document : Article/Communication Auteurs : Ludovic Moncla , Auteur ; Mauro Gaio, Auteur ; Javier Nogueras-Iso, Auteur ; Sébastien Mustière , Auteur Année de publication : 2016 Projets : 3-projet - voir note / Article en page(s) : pp 1137 - 1160 Note générale : Bibliographie
projet PerdidoLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] algorithme STA
[Termes IGN] analyse multicritère
[Termes IGN] approximation
[Termes IGN] arbre de décision
[Termes IGN] graphe
[Termes IGN] langage naturel (informatique)
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] traitement du langage naturelRésumé : (Auteur) Considerable amounts of geographical data are still collected not in form of GIS data but just as natural language texts. This paper proposes an approach for the automatic geocoding of itineraries described in natural language. This approach needs as an input a text annotated with part-of-speech and geo-semantic tags. The proposed method is divided into three main steps. First, we build a complete graph where vertices represent locations, and all vertices are connected to each other by undirected edges. We assign a weight to all the edges of the complete graph using a multi-criteria analysis approach. Then we compute a minimum spanning tree to obtain an undirected acyclic graph connecting all vertices. And finally, we transform this graph into a partially directed acyclic graph in order to identify the sequence of waypoints and build an approximation of a plausible footprint of the itinerary described. Additionally, the rationale of the proposed approach has been verified with a set of experiments on a corpus of hiking descriptions. Numéro de notice : A2016-297 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1108422 Date de publication en ligne : 09/11/2015 En ligne : https://doi.org/10.1080/13658816.2015.1108422 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80883
in International journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 1137 - 1160[article]Voir aussiRéservation
Réserver ce documentExemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-2016032 RAB Revue Centre de documentation En réserve L003 Disponible 079-2016031 RAB Revue Centre de documentation En réserve L003 Disponible Exploring cell tower data dumps for supervised learning-based point-of-interest prediction (industrial paper) / Ran Wang in Geoinformatica, vol 20 n° 2 (April - June 2016)
[article]
Titre : Exploring cell tower data dumps for supervised learning-based point-of-interest prediction (industrial paper) Type de document : Article/Communication Auteurs : Ran Wang, Auteur ; Chi-Yin Chow, Auteur ; Yan Lyu, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 327 - 349 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] algorithme d'apprentissage
[Termes IGN] apprentissage dirigé
[Termes IGN] comportement
[Termes IGN] données massives
[Termes IGN] exploration de données
[Termes IGN] histogramme
[Termes IGN] point d'intérêt
[Termes IGN] positionnement automatique
[Termes IGN] téléphonie mobile
[Termes IGN] utilisateurRésumé : (auteur) Exploring massive mobile data for location-based services becomes one of the key challenges in mobile data mining. In this paper, we investigate a problem of finding a correlation between the collective behavior of mobile users and the distribution of points of interest (POIs) in a city. Specifically, we use large-scale cell tower data dumps collected from cell towers and POIs extracted from a popular social network service, Weibo. Our objective is to make use of the data from these two different types of sources to build a model for predicting the POI densities of different regions in the covered area. An application domain that may benefit from our research is a business recommendation application, where a prediction result can be used as a recommendation for opening a new store/branch. The crux of our contribution is the method of representing the collective behavior of mobile users as a histogram of connection counts over a period of time in each region. This representation ultimately enables us to apply a supervised learning algorithm to our problem in order to train a POI prediction model using the POI data set as the ground truth. We studied 12 state-of-the-art classification and regression algorithms; experimental results demonstrate the feasibility and effectiveness of the proposed method. Numéro de notice : A2016-375 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Article DOI : 10.1007/s10707-015-0237-7 En ligne : http://dx.doi.org/10.1007/s10707-015-0237-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81140
in Geoinformatica > vol 20 n° 2 (April - June 2016) . - pp 327 - 349[article]Project pointless : pathfinding through identified empty space in point clouds / Tom Broersen in GIM international [en ligne], vol 30 n° 4 (April 2016)
[article]
Titre : Project pointless : pathfinding through identified empty space in point clouds Type de document : Article/Communication Auteurs : Tom Broersen, Auteur ; Florian W. Fichtner, Auteur ; Ivo de Liefde, Auteur Année de publication : 2016 Article en page(s) : pp 21 - 23 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espace intérieur vide
[Termes IGN] octree
[Termes IGN] semis de pointsRésumé : (éditeur) Indoor point clouds are useful for many applications, such as for pathfinding through empty, collision-free space. Fast-performing methods are required to identify this empty space because the indoor environment changes frequently and often does not follow the architectural design. As part of the Synthesis Project 2015, students of the MSc in Geomatics programme at Delft University of Technology have developed a method to efficiently identify and structure connected empty space in point clouds. Numéro de notice : A2016-214 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80681
in GIM international [en ligne] > vol 30 n° 4 (April 2016) . - pp 21 - 23[article]Street-side vehicle detection, classification and change detection using mobile laser scanning data / Wen Xiao in ISPRS Journal of photogrammetry and remote sensing, vol 114 (April 2016)
[article]
Titre : Street-side vehicle detection, classification and change detection using mobile laser scanning data Type de document : Article/Communication Auteurs : Wen Xiao, Auteur ; Bruno Vallet , Auteur ; Konrad Schindler, Auteur ; Nicolas Paparoditis , Auteur Année de publication : 2016 Projets : Terra Mobilita / Article en page(s) : pp 166 - 178 Note générale : bibliogaphie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage dirigé
[Termes IGN] classification dirigée
[Termes IGN] détection d'objet
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] modèle numérique d'objet
[Termes IGN] rectangle englobant minimum
[Termes IGN] semis de points
[Termes IGN] véhicule automobileRésumé : (auteur) Statistics on street-side car parks, e.g. occupancy rates, parked vehicle types, parking durations, are of great importance for urban planning and policy making. Related studies, e.g. vehicle detection and classification, mostly focus on static images or video. Whereas mobile laser scanning (MLS) systems are increasingly utilized for urban street environment perception due to their direct 3D information acquisition, high accuracy and movability. In this paper, we design a complete system for car park monitoring, including vehicle recognition, localization, classification and change detection, from laser scanning point clouds. The experimental data are acquired by an MLS system using high frequency laser scanner which scans the streets vertically along the system’s moving trajectory. The point clouds are firstly classified as ground, building façade, and street objects which are then segmented using state-of-the-art methods. Each segment is treated as an object hypothesis, and its geometric features are extracted. Moreover, a deformable vehicle model is fitted to each object. By fitting an explicit model to the vehicle points, detailed information, such as precise position and orientation, can be obtained. The model parameters are also treated as vehicle features. Together with the geometric features, they are applied to a supervised learning procedure for vehicle or non-vehicle recognition. The classes of detected vehicles are also investigated. Whether vehicles have changed across two datasets acquired at different times is detected to estimate the durations. Here, vehicles are trained pair-wisely. Two same or different vehicles are paired up as training samples. As a result, the vehicle recognition, classification and change detection accuracies are 95.9%, 86.0% and 98.7%, respectively. Vehicle modelling improves not only the recognition rate, but also the localization precision compared to bounding boxes. Numéro de notice : A2016--090 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.02.007 Date de publication en ligne : 03/03/2016 En ligne : http://doi.org/10.1016/j.isprsjprs.2016.02.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84612
in ISPRS Journal of photogrammetry and remote sensing > vol 114 (April 2016) . - pp 166 - 178[article]Octree-based segmentation for terrestrial LiDAR point cloud data in industrial applications / Yun-Ting Su in ISPRS Journal of photogrammetry and remote sensing, vol 113 (March 2016)
[article]
Titre : Octree-based segmentation for terrestrial LiDAR point cloud data in industrial applications Type de document : Article/Communication Auteurs : Yun-Ting Su, Auteur ; James Bethel, Auteur ; Shuowen Hu, Auteur Année de publication : 2016 Article en page(s) : pp 59 - 74 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] métrologie industrielle
[Termes IGN] octree
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestreRésumé : (auteur) Automated and efficient algorithms to perform segmentation of terrestrial LiDAR data is critical for exploitation of 3D point clouds, where the ultimate goal is CAD modeling of the segmented data. In this work, a novel segmentation technique is proposed, starting with octree decomposition to recursively divide the scene into octants or voxels, followed by a novel split and merge framework that uses graph theory and a series of connectivity analyses to intelligently merge components into larger connected components. The connectivity analysis, based on a combination of proximity, orientation, and curvature connectivity criteria, is designed for the segmentation of pipes, vessels, and walls from terrestrial LiDAR data of piping systems at industrial sites, such as oil refineries, chemical plants, and steel mills. The proposed segmentation method is exercised on two terrestrial LiDAR datasets of a steel mill and a chemical plant, demonstrating its ability to correctly reassemble and segregate features of interest. Numéro de notice : A2016-530 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.01.001 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.01.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81612
in ISPRS Journal of photogrammetry and remote sensing > vol 113 (March 2016) . - pp 59 - 74[article]Space–time adaptive processing and motion parameter estimation in multistatic passive radar using sparse Bayesian learning / Qisong Wu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)PermalinkPermalinkPermalinkPrediction of traffic counts using statistical and neural network models / Abul Kalam Azad in Geomatica, vol 69 n° 3 (september 2015)PermalinkComparing image-based methods for assessing visual clutter in generalized maps / Guillaume Touya in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W5 (October 2015)PermalinkChange-detection map learning using matching pursuit / Y. Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)PermalinkA novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree, Markov chain and cellular automata models in GIS / Abubrakr A. A. Al Sharif in Geocarto international, vol 30 n° 7 - 8 (August - September 2015)PermalinkAnalytical estimation of map readability / Lars Harrie in ISPRS International journal of geo-information, vol 4 n°2 (June 2015)PermalinkTerraMobilita/iQmulus urban point cloud analysis benchmark / Bruno Vallet in Computers and graphics, vol 49 (June 2015)PermalinkInterferometric phase image estimation via sparse coding in the complex domain / Hao Hongxing in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)PermalinkHyperspectral Band Selection by Multitask Sparsity Pursuit / Yuan Yuan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkPermalinkAutomatic spatial–spectral feature selection for hyperspectral image via discriminative sparse multimodal learning / Qian Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkPermalinkCharacterisation of building alignments with new measures using C4.5 decision tree algorithm / Sinan Cetinkaya in Geodetski vestnik, vol 58 n° 3 ([01/09/2014])PermalinkBi-temporal texton forest for land cover transition detection on remotely sensed imagery / Zhen Lei in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkDetecting subcanopy invasive plant species in tropical rainforest by integrating optical and microwave (InSAR/PolInSAR) remote sensing data, and a decision tree algorithm / Abduwasit Ghulam in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkActive learning of user’s preferences estimation towards a personalized 3D navigation of geo-referenced scenes / Christos Yiakoumettis in Geoinformatica, vol 18 n° 1 (January 2014)PermalinkMise à jour d’une base de données d’occupation du sol à grande échelle en milieux naturels à partir d’une image satellite THR / Adrien Gressin (2014)PermalinkReal-time generalization of point data in mobile and web mapping using quadtrees / Pia Bereuter in Cartography and Geographic Information Science, vol 40 n° 4 (September 2013)Permalink