Descripteur
Documents disponibles dans cette catégorie (1866)
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
A local structure and direction-aware optimization approach for three-dimensional tree modeling / Zhen Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)
[article]
Titre : A local structure and direction-aware optimization approach for three-dimensional tree modeling Type de document : Article/Communication Auteurs : Zhen Wang, Auteur ; Liqiang Zhang, Auteur ; Tian Fang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 4749 - 4757 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] optimisation (mathématiques)
[Termes IGN] reconstruction 3D
[Termes IGN] semis de points
[Termes IGN] squelettisationRésumé : (Auteur) Modeling 3-D trees from terrestrial laser scanning (TLS) point clouds remains a challenging task for several well-known reasons, including their complex structure and severe occlusions. In order to accurately reconstruct 3-D tree models from TLS point clouds that typically suffer from significant occlusions, in this paper, a novel local structure and direction-aware approach is presented to successfully complete missing structures of trees. In this method, we first extract the coarse tree skeleton from the input point cloud, and thus, the branch dominant direction and the point density of each branch are obtained. By a skeleton-based Laplacian algorithm, the point cloud is further shrunk into a skeleton point cloud to highlight the branch dominant direction of each branch. For obtaining even more accurate point densities, a dictionary-based algorithm is utilized to learn and reconstruct the local structure. Finally, the branch dominant direction and point density are integrated into an iterative optimization process to recover the missing data. Extensive experimental results have shown that the proposed method is very robust to incomplete data sets, and it is capable of accurately reconstructing 3-D trees, which are partially, or even to a large extent, missing from the input point cloud. Numéro de notice : A2016-890 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2551286 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2551286 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83070
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4749 - 4757[article]Magnetic induction-based positioning in distorted environments / Orfeas Kypris in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)
[article]
Titre : Magnetic induction-based positioning in distorted environments Type de document : Article/Communication Auteurs : Orfeas Kypris, Auteur ; Traian E. Abrudan, Auteur ; Andrew Markham, Auteur Année de publication : 2016 Article en page(s) : pp 4605 - 4612 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] champ magnétique
[Termes IGN] induction magnétique
[Termes IGN] métal
[Termes IGN] méthode des éléments finis
[Termes IGN] modèle analytique
[Termes IGN] positionnement en intérieurRésumé : (Auteur) Ferrous and highly conductive materials distort low-frequency magnetic fields and can significantly increase magnetoinductive positioning errors. In this paper, we use the image theory in order to formulate an analytical channel model for the magnetic field of a quasi-static magnetic dipole positioned above a perfectly conducting half-space. The proposed model can be used to compensate for the distorting effects that metallic reinforcement bars (rebars) within the floor impose on the magnetic field of a magnetoinductive transmitter node in an indoor single-story environment. Good agreement is observed between the analytical solution and numerical solutions obtained from 3-D finite-element simulations. Experimental results indicate that the image theory model shows improvement over the free-space dipole model in estimating positions in the distorted environment, typically reducing positioning errors by 22% in 90% of the cases and 26% in 40% of the cases. No prior information on the geometry of the metallic distorters was available, making this essentially a “blind” technique. Numéro de notice : A2016-887 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2546461 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2546461 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83067
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4605 - 4612[article]Simultaneously sparse and low-rank abundance matrix estimation for hyperspectral image unmixing / Paris V. Giampouras in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)
[article]
Titre : Simultaneously sparse and low-rank abundance matrix estimation for hyperspectral image unmixing Type de document : Article/Communication Auteurs : Paris V. Giampouras, Auteur ; Konstantinos E. Themelis, Auteur ; Athanasios A. Rontogiannis, Auteur ; Konstantinos D. Koutroumbas, Auteur Année de publication : 2016 Article en page(s) : pp 4775 - 4789 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] données clairsemées
[Termes IGN] image hyperspectrale
[Termes IGN] matrice creuseRésumé : (Auteur) In a plethora of applications dealing with inverse problems, e.g., image processing, social networks, compressive sensing, and biological data processing, the signal of interest is known to be structured in several ways at the same time. This premise has recently guided research into the innovative and meaningful idea of imposing multiple constraints on the unknown parameters involved in the problem under study. For instance, when dealing with problems whose unknown parameters form sparse and low-rank matrices, the adoption of suitably combined constraints imposing sparsity and low rankness is expected to yield substantially enhanced estimation results. In this paper, we address the spectral unmixing problem in hyperspectral images. Specifically, two novel unmixing algorithms are introduced in an attempt to exploit both spatial correlation and sparse representation of pixels lying in the homogeneous regions of hyperspectral images. To this end, a novel mixed penalty term is first defined consisting of the sum of the weighted ℓ1 and the weighted nuclear norm of the abundance matrix corresponding to a small area of the image determined by a sliding square window. This penalty term is then used to regularize a conventional quadratic cost function and impose simultaneous sparsity and low rankness on the abundance matrix. The resulting regularized cost function is minimized by: 1) an incremental proximal sparse and low-rank unmixing algorithm; and 2) an algorithm based on the alternating direction method of multipliers. The effectiveness of the proposed algorithms is illustrated in experiments conducted both on simulated and real data. Numéro de notice : A2016-891 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2551327 En ligne : https://doi.org/10.1109/TGRS.2016.2551327 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83071
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4775 - 4789[article]Sparse output coding for scalable visual recognition / Bin Zhao in International journal of computer vision, vol 119 n° 1 (August 2016)
[article]
Titre : Sparse output coding for scalable visual recognition Type de document : Article/Communication Auteurs : Bin Zhao, Auteur ; Eric P. Xing, Auteur Année de publication : 2016 Article en page(s) : pp 60 - 75 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification
[Termes IGN] codage
[Termes IGN] décodage
[Termes IGN] matrice
[Termes IGN] reconnaissance d'objetsRésumé : (auteur) Many vision tasks require a multi-class classifier to discriminate multiple categories, on the order of hundreds or thousands. In this paper, we propose sparse output coding, a principled way for large-scale multi-class classification, by turning high-cardinality multi-class categorization into a bit-by-bit decoding problem. Specifically, sparse output coding is composed of two steps: efficient coding matrix learning with scalability to thousands of classes, and probabilistic decoding. Empirical results on object recognition and scene classification demonstrate the effectiveness of our proposed approach. Numéro de notice : A2016--152 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s11263-015-0839-4 En ligne : https://doi.org/10.1007/s11263-015-0839-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85920
in International journal of computer vision > vol 119 n° 1 (August 2016) . - pp 60 - 75[article]A bootstrap test for constant coefficients in geographically weighted regression models / Chang-Lin Mei in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)
[article]
Titre : A bootstrap test for constant coefficients in geographically weighted regression models Type de document : Article/Communication Auteurs : Chang-Lin Mei, Auteur ; Min Xu, Auteur ; Ning Wang, Auteur Année de publication : 2016 Article en page(s) : pp 1622 - 1643 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] base de données déductive
[Termes IGN] Bootstrap (EDI)
[Termes IGN] inférence statistique
[Termes IGN] modèle de régression
[Termes IGN] processeur
[Termes IGN] régression géographiquement pondérée
[Termes IGN] test de performanceRésumé : (Auteur) Statistical tests for whether some coefficients really vary over space play an important role in using the geographically weighted regression (GWR) to explore spatial non-stationarity of the regression relationship. In view of some shortcomings of the existing inferential methods, we propose a residual-based bootstrap test to detect the constant coefficients in a GWR model. The proposed test is free of the assumption that the model error term is normally distributed and admits some useful extensions for identifying more complicated spatial patterns of the coefficients. Some simulation with comparison to the existing test methods is conducted to assess the test performance, including the accuracy of the bootstrap approximation to the null distribution of the test statistic, the power in identifying spatially varying coefficients and the robustness to collinearity among the explanatory variables. The simulation results demonstrate that the bootstrap test works quite well. Furthermore, a real-world data set is analyzed to illustrate the application of the proposed test. Numéro de notice : A2016-320 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1149181 En ligne : http://dx.doi.org/10.1080/13658816.2016.1149181 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80940
in International journal of geographical information science IJGIS > vol 30 n° 7- 8 (July - August 2016) . - pp 1622 - 1643[article]Réservation
Réserver ce documentExemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-2016042 RAB Revue Centre de documentation En réserve L003 Disponible 079-2016041 RAB Revue Centre de documentation En réserve L003 Disponible Estimating the intrinsic dimension of hyperspectral images using a noise-whitened eigengap approach / Abderrahim Halimi in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)PermalinkGeographically weighted evidence combination approaches for combining discordant and inconsistent volunteered geographical information / Alexis Comber in Geoinformatica, vol 20 n° 3 (July - September 2016)PermalinkLocation K-anonymity in indoor spaces / Joon-Seok Kim in Geoinformatica, vol 20 n° 3 (July - September 2016)PermalinkRecursive orthogonal projection-based simplex growing algorithm / Hsiao-Chi Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)PermalinkRobust high-quality interpolation of regions to moving regions / Florian Heinz in Geoinformatica, vol 20 n° 3 (July - September 2016)PermalinkSparse and low-rank graph for discriminant analysis of hyperspectral imagery / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)PermalinkTask selection in spatial crowdsourcing from worker’s perspective / Dingxiong Deng in Geoinformatica, vol 20 n° 3 (July - September 2016)PermalinkSpectral band selection for urban material classification using hyperspectral libraries / Arnaud Le Bris in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-7 (July 2016)PermalinkFusion of hyperspectral and VHR multispectral image classifications in urban α–areas / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-3 (July 2016)PermalinkIntegrating risk preferences in forest harvest scheduling / Kyle J. Eyvindson in Annals of Forest Science, vol 73 n° 2 (June 2016)PermalinkMesure de robustesse d'un réseau géodésique 3D : cas du réseau GPS de la ville d'Oran (Algérie) / Bachir Gourine in XYZ, n° 147 (juin - août 2016)PermalinkOptimization of observation plan based on the stochastic characteristics of the geodetic network / Wojciech Pachelski in Reports on geodesy and geoinformatics, vol 101 (June 2016)PermalinkVariants of the empirical interpolation method: symmetric formulation, choice of norms and rectangular extension / Fabien Casenave in Applied Mathematics Letters, vol 56 (June 2016)PermalinkVector attribute profiles for hyperspectral image classification / Erchan Aptoula in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)PermalinkReconstruction of the vertical electron density profile based on vertical TEC using the simulated annealing algorithm / Chunhua Jiang in Advances in space research, vol 57 n° 10 (May 2016)PermalinkAn effective toolkit for the interpolation and gross error detection of GPS time series / X. Wang in Survey review, vol 48 n° 348 (May 2016)PermalinkAn improved ANUDEM method combining topographic correction and DEM interpolation / Xianwei Zheng in Geocarto international, vol 31 n° 5 - 6 (May - June 2016)PermalinkKinematic interpolation of movement data / Jed A. Long in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkReconstruction 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)PermalinkSimulating urban growth processes by integrating cellular automata model and artificial optimization in Binhai New Area of Tianjin, China / Fengmei Yao in Geocarto international, vol 31 n° 5 - 6 (May - June 2016)Permalink