Descripteur
Termes IGN > mathématiques > statistique mathématique > analyse de données > analyse multivariée > analyse factorielle > analyse de groupement
analyse de groupementSynonyme(s)analyse par segmentation analyse des groupesVoir aussi |
Documents disponibles dans cette catégorie (157)
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
Semisupervised classification of remote sensing images with active queries / Jordi Munoz-Mari in IEEE Transactions on geoscience and remote sensing, vol 50 n° 10 Tome 1 (October 2012)
[article]
Titre : Semisupervised classification of remote sensing images with active queries Type de document : Article/Communication Auteurs : Jordi Munoz-Mari, Auteur ; Devis Tuia, Auteur ; G. Camps-Valls, Auteur Année de publication : 2012 Article en page(s) : pp 3751 - 3763 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage (cognition)
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte de confiance
[Termes IGN] classification semi-dirigée
[Termes IGN] image multibande
[Termes IGN] occupation du sol
[Termes IGN] requête spatiale
[Termes IGN] télédétection spatialeRésumé : (Auteur) We propose a semiautomatic procedure to generate land cover maps from remote sensing images. The proposed algorithm starts by building a hierarchical clustering tree, and exploits the most coherent pixels with respect to the available class information. For a given amount of labeled pixels, the algorithm returns both classification and confidence maps. Since the quality of the map depends of the number and informativeness of the labeled pixels, active learning methods are used to select the most informative samples to increase confidence in class membership. Experiments on four different data sets, accounting for hyperspectral and multispectral images at different spatial resolutions, confirm the effectiveness of the proposed approach, and how active learning techniques reduce the uncertainty of the classification maps. Specifically, more accurate results with fewer labeled samples are obtained. Inclusion of spatial information in the classifiers drastically improves the classification accuracy, leading to faster convergence curves and tighter confidence intervals. In conclusion, the presented algorithm provides efficient image classification and, at the same time, yields a confidence map that may be very useful in many Earth observation applications. Numéro de notice : A2012-524 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2185504 Date de publication en ligne : 08/03/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2185504 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31970
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 10 Tome 1 (October 2012) . - pp 3751 - 3763[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2012101A RAB Revue Centre de documentation En réserve L003 Disponible Hyperspectral band clustering and band selection for urban land cover classification / H. Su in Geocarto international, vol 27 n° 5 (August 2012)
[article]
Titre : Hyperspectral band clustering and band selection for urban land cover classification Type de document : Article/Communication Auteurs : H. Su, Auteur ; Q. Du, Auteur Année de publication : 2012 Article en page(s) : pp 39 - 411 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification semi-dirigée
[Termes IGN] image hyperspectrale
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] précision de la classification
[Termes IGN] signature spectrale
[Termes IGN] valeur aberranteRésumé : (Auteur) The aim of this study is to combine band clustering with band selection for dimensionality reduction of hyperspectral imagery. The performance of dimensionality reduction is evaluated through urban land cover classification accuracy with the dimensionality-reduced data. Different from unsupervised clustering using all the pixels or supervised clustering requiring labelled pixels, the discussed semi-supervised band clustering needs class spectral signatures only; band selection result is used as initial condition for band clustering; after clustering, a cluster selection step is applied to select clusters to be used in the following data analysis. In this article, we propose to conduct band selection by removing outlier bands in each cluster before finalizing cluster centres. The experimental results in urban land cover classification show that the proposed algorithm can further enhance support vector machine (SVM)-based classification accuracy. Numéro de notice : A2012-370 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.643322 Date de publication en ligne : 12/01/2012 En ligne : https://doi.org/10.1080/10106049.2011.643322 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31816
in Geocarto international > vol 27 n° 5 (August 2012) . - pp 39 - 411[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2012051 RAB Revue Centre de documentation En réserve L003 Disponible Memory-based cluster sampling for remote sensing image classification / Michele Volpi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
[article]
Titre : Memory-based cluster sampling for remote sensing image classification Type de document : Article/Communication Auteurs : Michele Volpi, Auteur ; Devis Tuia, Auteur ; Mikhail Kanevski, Auteur Année de publication : 2012 Article en page(s) : pp 3096 - 3106 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage automatique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image à très haute résolution
[Termes IGN] image hyperspectraleRésumé : (Auteur) In this paper, we address the problem of semi-automatic definition of training sets for the classification of remotely sensed images. We propose two approaches based on active learning aiming at removing both the proximal (low diversity) and the dense (low exploration during iterations) sampling redundancies. The first is encountered when several samples carrying similar spectral information are selected by the algorithm, while the second occurs when the heuristic is unable to explore undiscovered parts of the feature space during iterations. For this purpose, kernel k-means is used to cluster a set of uncertain candidates in the same space spanned by the kernel function defined in the SVM classification step. Two heuristics are proposed to maximize the speed of convergence to high classification accuracies: The first is based on binary hierarchical partitioning of the set of selected uncertain samples, while the second extends this approach by considering memory in the selection and thus dynamically adapts to the problem throughout the iterations. Experiments on both VHR and hyperspectral imagery confirm fast convergence of the algorithm, that outperforms state-of-the-art sampling schemes. Numéro de notice : A2012-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2179661 Date de publication en ligne : 21/02/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2179661 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31829
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3096 - 3106[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2012081 RAB Revue Centre de documentation En réserve L003 Disponible Satellite image time series analysis under time warping / F. Petitjean in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
[article]
Titre : Satellite image time series analysis under time warping Type de document : Article/Communication Auteurs : F. Petitjean, Auteur ; Jordi Inglada, Auteur ; Pierre Gançarski, Auteur Année de publication : 2012 Article en page(s) : pp 3081 - 3095 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] déformation temporelle dynamique (algorithme)
[Termes IGN] échantillon
[Termes IGN] image optique
[Termes IGN] série temporelleRésumé : (Auteur) Satellite Image Time Series are becoming increasingly available and will continue to do so in the coming years thanks to the launch of space missions which aim at providing a coverage of the Earth every few days with high spatial resolution. In the case of optical imagery, it will be possible to produce land use and cover change maps with detailed nomenclatures. However, due to meteorological phenomena, such as clouds, these time series will become irregular in terms of temporal sampling, and one will need to compare time series with different lengths. In this paper, we present an approach to image time series analysis which is able to deal with irregularly sampled series and which also allows the comparison of pairs of time series where each element of the pair has a different number of samples. We present the dynamic time warping from a theoretical point of view and illustrate its capabilities with two applications to real-time series. Numéro de notice : A2012-382 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2179050 Date de publication en ligne : 31/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2179050 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31828
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3081 - 3095[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2012081 RAB Revue Centre de documentation En réserve L003 Disponible Trees detection from laser point clouds acquired in dense urban areas by a mobile mapping system / Fabrice Monnier in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)
[article]
Titre : Trees detection from laser point clouds acquired in dense urban areas by a mobile mapping system Type de document : Article/Communication Auteurs : Fabrice Monnier , Auteur ; Bruno Vallet , Auteur ; Bahman Soheilian , Auteur Année de publication : 2012 Article en page(s) : pp 245 - 250 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse de groupement
[Termes IGN] détection d'arbres
[Termes IGN] détection de partie cachée
[Termes IGN] données lidar
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconstruction 3D
[Termes IGN] scène urbaine
[Termes IGN] semis de points
[Termes IGN] système de numérisation mobileRésumé : (auteur) 3D reconstruction of trees is of great interest in large-scale 3D city modelling. Laser scanners provide geometrically accurate 3D point clouds that are very useful for object recognition in complex urban scenes. Trees often cause important occlusions on building façades. Their recognition can lead to occlusion maps that are useful for many façade oriented applications such as visual based localisation and automatic image tagging. This paper proposes a pipeline to detect trees in point clouds acquired in dense urban areas with only laser informations (x,y, z coordinates and intensity). It is based on local geometric descriptors computed on each laser point using a determined neighbourhood. These descriptors describe the local shape of objects around every 3D laser point. A projection of these values on a 2D horizontal accumulation space followed by a combination of morphological filters provides individual tree clusters. The pipeline is evaluated and the results are presented on a set of one million laser points using a man made ground truth. Numéro de notice : A2012-764 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-I-3-245-2012 Date de publication en ligne : 20/07/2012 En ligne : https://doi.org/10.5194/isprsannals-I-3-245-2012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101276
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol I-3 (2012) . - pp 245 - 250[article]Discovering spatial patterns in origin-destination mobility data / D. Guo in Transactions in GIS, vol 16 n° 3 (June 2012)PermalinkEfficient parallel algorithm for pixel classification in remote sensing imagery / U. Maulik in Geoinformatica, vol 16 n° 2 (April 2012)PermalinkFuzzy analysis for modeling regional delineation and development: The case of the Sardinian mining geopark / G. Manca in Transactions in GIS, vol 16 n° 1 (February 2012)PermalinkClustering of detected changes in high-resolution satellite imagery using a stabilized competitive agglomeration algorithm / O. Sjahputera in IEEE Transactions on geoscience and remote sensing, vol 49 n° 12 Tome 1 (December 2011)PermalinkComputational method for the point cluster analysis on networks / K. Sugihara in Geoinformatica, vol 15 n° 1 (January 2011)PermalinkA framework for regional association rule mining and scoping in spatial datasets / W. Ding in Geoinformatica, vol 15 n° 1 (January 2011)PermalinkL’impact du voisinage géographique des pays dans l’attribution des votes au Concours Eurovision de la Chanson / Jean-François Gleyze in Cybergeo, European journal of geography, n° 2011 ([01/01/2011])PermalinkUsing clustering methods in geospatial information systems / X. Wang in Geomatica, vol 64 n° 3 (September 2010)PermalinkSegmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds / A. Sampath in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)PermalinkAutomatic cluster identification for environnemental applications using the self-organizing maps and a new genetic algorithm / T. Oyana in Geocarto international, vol 25 n° 1 (February 2010)Permalink