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Auteur Nesrine Chehata
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PhD student at MATIS, from 2001 to 2005 - then, research fellow at LASTIG
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Identify important spectrum bands for classification using importances of wrapper selection applied to hyperspectral data / Arnaud Le Bris (2014)
Titre : Identify important spectrum bands for classification using importances of wrapper selection applied to hyperspectral data Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata , Auteur ; Xavier Briottet , Auteur ; Nicolas Paparoditis , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : IWCIM 2014, International Workshop on Computational Intelligence for Multimedia Understanding 01/11/2014 02/11/2014 Paris France Proceedings IEEE Importance : pp Note générale : bibliographie Langues : Anglais (eng) Résumé : (auteur) Intermediate results of two state-of-the-art wrapper feature selection approaches (GA and SFFS) applied to hyperspectral data sets were used to derive information about band importance for specific land cover classification problems. Several feature selection performance scores (classification accuracies, Bhattacharyya separability) were tested. The impact of the number of selected bands on classification accuracy was obtained thanks to SFFS, while a band importance measure was derived from intermediate sets of bands tested by GA. Such results are a first step toward the identification of the most suitable spectral bands to design superspectral camera systems dedicated to specific applications (e.g. classification of urban land cover and material maps). Numéro de notice : C2014-021 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IWCIM.2014.7008806 Date de publication en ligne : 15/01/2015 En ligne : http://dx.doi.org/10.1109/IWCIM.2014.7008806 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83403 Large scale road network extraction in forested moutainous areas using airborne laser scanning data / António Ferraz (2014)
Titre : Large scale road network extraction in forested moutainous areas using airborne laser scanning data Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Clément Mallet , Auteur ; Nesrine Chehata , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : IGARSS 2014, International Geoscience And Remote Sensing Symposium 13/07/2014 18/07/2014 Québec Québec - Canada Proceedings IEEE Importance : pp 4315 - 4318 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction du réseau routier
[Termes IGN] forêt alpestre
[Termes IGN] France (administrative)
[Termes IGN] montagne
[Termes IGN] processus ponctuel marqué
[Termes IGN] reconnaissance de formes
[Termes IGN] théorie des graphesRésumé : (auteur) In this work, we present an approach that is able to deal with large-scale road network mapping. While former methods focus on delineating patches of roads without computing a coherent road network, we formulate a very large number of road hypothesis that are pruned using a graph reasoning and weak a priori knowledge on road behavior. The initial solution is computed by means of two machine learning and pattern recognition state-of-the-art methods (namely, Random Forest classification and Marked Point Process) that allow to process very large areas in little time with very satisfactory results. Numéro de notice : C2014-024 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2014.6947444 Date de publication en ligne : 06/11/2014 En ligne : http://dx.doi.org/10.1109/IGARSS.2014.6947444 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92029 Documents numériques
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Large scale road network extraction... - pdf auteurAdobe Acrobat PDF Use intermediate results of wrapper band selection methods: A first step toward the optimization of spectral configuration for land cover classifications / Arnaud Le Bris (2014)
Titre : Use intermediate results of wrapper band selection methods: A first step toward the optimization of spectral configuration for land cover classifications Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata , Auteur ; Xavier Briottet , Auteur ; Nicolas Paparoditis , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : WHISPERS 2014, 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing 24/06/2014 27/06/2014 Lausanne Suisse Proceedings IEEE Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image hyperspectrale
[Termes IGN] zone urbaineRésumé : (auteur) Intermediate results of two state-of-the-art wrapper feature selection approaches (GA and SFFS) associated to a classifier (linear SVM) applied to hyperspectral data sets were used to derive information about band importance for specific land cover classification problems. The impact of the number of selected bands on classification accuracy was obtained thanks to SFFS, while a band importance measure was derived from intermediate sets of bands tested by GA. Such results are a first step toward the identification of the most suitable spectral bands to design superspectral camera systems dedicated to specific applications (e.g. classification of urban land cover and material maps). Numéro de notice : C2014-042 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/WHISPERS.2014.8077653 Date de publication en ligne : 26/10/2017 En ligne : https://doi.org/10.1109/WHISPERS.2014.8077653 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99587 Documents numériques
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Use intermediate results ... - pdf auteurAdobe Acrobat PDF Large-scale classification of water areas using airborne topographic lidar data / Julien Smeeckaert in Remote sensing of environment, vol 138 (November 2013)
[article]
Titre : Large-scale classification of water areas using airborne topographic lidar data Type de document : Article/Communication Auteurs : Julien Smeeckaert, Auteur ; Clément Mallet , Auteur ; Nicolas David , Auteur ; Nesrine Chehata , Auteur ; António Ferraz , Auteur Année de publication : 2013 Article en page(s) : pp 134 - 148 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] grande échelle
[Termes IGN] littoral
[Termes IGN] modèle numérique de terrain
[Termes IGN] rive
[Termes IGN] rivière
[Termes IGN] semis de points
[Termes IGN] trait de côteRésumé : (auteur) Accurate Digital Terrain Models (DTMs) are inevitable inputs for mapping and analyzing areas subject to natural hazards. Topographic airborne laser scanning has become an established technique to characterize the Earth's surface: lidar provides 3D point clouds allowing for a fine reconstruction of the topography while preserving high frequencies of the relief. For flood hazard modeling, the key step, before going onto terrain modeling, is the discrimination of land and water areas within the delivered point clouds. Therefore, instantaneous shorelines, river banks, and inland waters can be extracted as a basis for more reliable DTM generation. This paper presents an automatic, efficient, and versatile workflow for land/water classification of airborne topographic lidar points, effective at large scales (>300 km2). For that purpose, the Support Vector Machine (SVM) method is used as a classification framework and it is embedded in a workflow designed for our specific goal. First, a restricted but carefully designed set of features, based only on 3D lidar point coordinates and flightline information, is defined as classifier input. Then, the SVM learning step is performed on small but well-targeted areas thanks to a semiautomatic region growing strategy. Finally, label probability output by SVM is merged with contextual knowledge during a probabilistic relaxation step in order to remove pixel-wise misclassification. Results show that a survey of hundreds of millions of points are labeled with high accuracy (>95% in most cases for coastal areas, and >90% for rivers) and that small natural and anthropic features of interest are still well classified even though we work at lowpoint densities (0.5–4 pts/m2). We also noticed that it may fail in water-logged areas. Nevertheless, our approach remains valid for regional and national mapping purposes, coasts and rivers, and provides a strong basis for further discrimination of land-cover classes and coastal habitats. Numéro de notice : A2013-792 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2013.07.004 Date de publication en ligne : 15/08/2013 En ligne : https://doi.org/10.1016/j.rse.2013.07.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80174
in Remote sensing of environment > vol 138 (November 2013) . - pp 134 - 148[article]Comparison of VHR panchromatic texture features for tillage mapping / Nesrine Chehata (juillet 2013)
Titre : Comparison of VHR panchromatic texture features for tillage mapping Type de document : Article/Communication Auteurs : Nesrine Chehata , Auteur ; Arnaud Le Bris , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : juillet 2013 Conférence : IGARSS 2013, International Geoscience And Remote Sensing Symposium 21/07/2013 26/07/2013 Melbourne Australie Proceedings IEEE Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] carte agricole
[Termes IGN] image à très haute résolution
[Termes IGN] image panchromatiqueNuméro de notice : C2013-027 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2013.6723489 Date de publication en ligne : 27/01/2014 En ligne : https://doi.org/10.1109/IGARSS.2013.6723489 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80105 Contribution of texture and red-edge band for vegetated areas detection and identification / Arnaud Le Bris (2013)PermalinkLarge-scale water classification of coastal areas using airborne topographic lidar data / Julien Smeeckaert (juillet 2013)PermalinkVery high resolution urban land cover extraction using airborne hyperspectral images / Arnaud Le Bris (April 2013)PermalinkChange detection in a topographic building database using submetric satellite images / Arnaud Le Bris (2011)PermalinkRelevance of airborne lidar and multispectral image data for urban scene classification using random forests / Li Guo in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 1 (January - February 2011)PermalinkTerrain modeling from Lidar range data in natural landscapes: a predictive and Bayesian framework / Frédéric Bretar in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)PermalinkExtraction of vertical posts in 3D laser point clouds acquired in dense urban areas by a mobile mapping system / Sterenn Liberge (2010)PermalinkPermalinkA two-pass random forests classification of airborne Lidar and image data on urban scenes / Li Guo (2010)PermalinkContribution of airborne full-waveform Lidar and image data for urban scene classification / Nesrine Chehata (07/11/2009)Permalink