Centre de documentation
scientifique

Representative multiple Kernel learning for classification in hyperspectral imagery / Y. Gu in IEEE Transactions on geoscience and remote sensing, vol 50 n° 7 Tome 2 (July 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 7 Tome 2 (July 2012) . - pp 2852 - 2865 Titre : Representative multiple Kernel learning for classification in hyperspectral imagery Type de document : Article/Communication Auteurs : Y. Gu, Auteur ; C. Wang, Auteur ; D. You, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 2852 - 2865 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage automatique [Termes IGN] image hyperspectrale [Termes IGN] méthode fondée sur le noyau Résumé : (Auteur) Recently, multiple kernel learning (MKL) methods have been developed to improve the flexibility of kernel-based learning machine. The MKL methods generally focus on determining key kernels to be preserved and their significance in optimal kernel combination. Unfortunately, computational demand of finding the optimal combination is prohibitive when the number of training samples and kernels increase rapidly, particularly for hyperspectral remote sensing data. In this paper, we address the MKL for classification in hyperspectral images by extracting the most variation from the space spanned by multiple kernels and propose a representative MKL (RMKL) algorithm. The core idea embedded in the algorithm is to determine the kernels to be preserved and their weights according to statistical significance instead of time-consuming search for optimal kernel combination. The noticeable merits of RMKL consist that it greatly reduces the computational load for searching optimal combination of basis kernels and has no limitation from strict selection of basis kernels like most MKL algorithms do; meanwhile, RMKL keeps excellent properties of MKL in terms of both good classification accuracy and interpretability. Experiments are conducted on different real hyperspectral data, and the corresponding experimental results show that RMKL algorithm provides the best performances to date among several the state-of-the-art algorithms while demonstrating satisfactory computational efficiency. Numéro de notice : A2012-322 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2176341 Date de publication en ligne : 17/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2176341 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31768 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2012071B	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Pattern 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)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 6 (June 2007) . - pp 663 - 670 Titre : Pattern matching for heterogeneous geodata sources using attributed relational graph and probabilistic relaxation Type de document : Article/Communication Auteurs : S. Yi, Auteur ; B. Huang, Auteur ; C. Wang, Auteur Année de publication : 2007 Article en page(s) : pp 663 - 670 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] appariement de formes [Termes IGN] données hétérogènes [Termes IGN] données multisources [Termes IGN] graphe relationnel [Termes IGN] information sémantique [Termes IGN] modèle sémantique de données Résumé : (Auteur) Information retrieval and intelligent search among heterogeneous data sources still continue to be challenging tasks. In this study, an attributed relational graph was employed to model the semantic information of heterogeneous geodata sources. Based on the attributed relational graphs, probabilistic relaxation was employed for pattern matching between different data sources. The initial probability and compatibility coefficients were calculated based on the combined evidence from semi-structured geodata sources and the characteristics of discrete and categorical variables. Experiments on automatic pattern matching were carried out and the results demonstrated the effectiveness of the proposed approach in element mapping between heterogeneous data sources. Copyright ASPRS Numéro de notice : A2007-297 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.6.663 En ligne : http://dx.doi.org/10.14358/PERS.73.6.663 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28660 [article]

Typhoon insurance pricing with spatial decision support tools / L. Li in International journal of geographical information science IJGIS, vol 19 n° 3 (march 2005)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 19 n° 3 (march 2005) . - pp 363 - 384 Titre : Typhoon insurance pricing with spatial decision support tools Type de document : Article/Communication Auteurs : L. Li, Auteur ; Jing Wang, Auteur ; C. Wang, Auteur Année de publication : 2005 Article en page(s) : pp 363 - 384 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse de données [Termes IGN] assurance [Termes IGN] Chine [Termes IGN] Component Object Model [Termes IGN] coût [Termes IGN] cyclone [Termes IGN] données thématiques [Termes IGN] exploration de données [Termes IGN] interface logicielle [Termes IGN] logiciel libre [Termes IGN] logique floue [Termes IGN] outil d'aide à la décision [Termes IGN] risque naturel [Termes IGN] simulation [Termes IGN] système d'information géographique [Termes IGN] système de gestion de base de données [Termes IGN] visualisation [Termes IGN] vulnérabilité Résumé : (Auteur) In disaster insurance and reinsurance, GIS has been used to visualize and manage geospatial data and to help vulnerability and risk analysis for years. However, hazard insurance is a multidisciplinary issue that involves complex factors and uncertainty. GIS, if used alone, has limited functionality due to poor incorporation of intelligence and spatial statistics. The Spatial Decision Support System (SDSS) presented in this paper, addresses some of the deficiencies of traditional GIS, by providing powerful tools to support disaster insurance pricing that involves procedural and declarative knowledge. In the SDSS, the knowledge-based system shell, using the open-source CLIPS and supporting fuzziness and uncertainty, can be applied in at least three phases: hazard simulation, fuzzy comprehensive evaluation of risk, and query for insurance pricing. The libraries of statistics and spatial statistics provide a robust support for analysis of spatial factors, including spatial correlation between zones vulnerable to hazard and spatial variation of exposures. The GIS components provide sophisticated visualization and database management support for geospatial data, helping easily locate the insured points and risk zones as well as exploratory analysis of spatial data. Standard database management interfaces are used to manage other aspatial data. COM, an industry-wide interface protocol, tightly integrates these technologies (the expert shell, GIS, spatial statistics and DBM within an integral system), and can be used to develop mixed complex algorithms in support of other COM objects. An application of typhoon insurance pricing is demonstrated with a case study in Guangdong, China. Developed as a suite of generic tools with abilities to deal with the complex problem of disaster insurance involving spatial factors and field knowledge, this prototype SDSS can also be applied to other disaster insurance and fields that involve similar spatial decision making. Numéro de notice : A2005-080 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810412331317742 En ligne : https://doi.org/10.1080/13658810412331317742 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27218 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-05031	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-05032	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Applying SAR Interferometry for ground deformation detection in China / C. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 10 (October 2004)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 10 (October 2004) . - pp 1157 - 1165 Titre : Applying SAR Interferometry for ground deformation detection in China Type de document : Article/Communication Auteurs : C. Wang, Auteur ; H. Zhang, Auteur ; X. Shan, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 1157 - 1165 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] Chine [Termes IGN] déformation de la croute terrestre [Termes IGN] image radar moirée [Termes IGN] interferométrie différentielle [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] milieu urbain [Termes IGN] risque naturel [Termes IGN] séisme [Termes IGN] subsidence [Termes IGN] surveillance géologique Résumé : (Auteur) This paper applies SAR Interferometry for ground deformation in two cases: the 1998 Zhangbei-Shangyi Earthquake in Northern China and the urban subsidence in Suzhou City from 1993 to 2000. It is concluded that SAR interferometry may provide valuable information for understanding the spatial patterns and progress of natural hazards. SAR interferometry is also critical for mechanism studies and hazard mitigation. Numéro de notice : A2004-363 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.70.10.1157 En ligne : https://doi.org/10.14358/PERS.70.10.1157 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26890 [article]