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Automatic 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)
[article]
Titre : Automatic spatial–spectral feature selection for hyperspectral image via discriminative sparse multimodal learning Type de document : Article/Communication Auteurs : Qian Zhang, Auteur ; Yuan Tian, Auteur ; Yuan Yang, Auteur ; Chunhong Pan, Auteur Année de publication : 2015 Article en page(s) : pp 261 - 279 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] apprentissage (cognition)
[Termes IGN] apprentissage dirigé
[Termes IGN] classification spectrale
[Termes IGN] image hyperspectrale
[Termes IGN] matrice
[Termes IGN] méthode des moindres carrés
[Termes IGN] programmation non linéaireRésumé : (Auteur) Spectral-spatial feature combination for hyperspectral image analysis has become an important research topic in hyperspectral remote sensing applications. A simple and straightforward way to integrate spectral-spatial features is to concatenate heterogeneous features into a long vector. Then, the dimensionality reduction techniques, i.e., feature selection, are applied before subsequent utilizations. However, such representation can introduce redundancy and noise. Moreover, traditional single-feature selection methods treat different features equally and ignore their complementary properties. As a result, the performance of subsequent tasks, i.e., classification, would drop down. In this paper, we propose a novel approach to integrate the spectral-spatial features based on the concatenating strategy, termed discriminative sparse multimodal learning for feature selection (DSML-FS). In the proposed method, joint structured sparsity regularizations are used to exploit the intrinsic data structure and relationships among different features. Discriminative least squares regression is applied to enlarge the distance between classes. Therefore, the weight matrix incorporating the information of feature wise and individual properties is automatically learned for spectral-spatial feature selection. We develop an alternative iterative algorithm to solve the nonlinear optimization problem in DSML-FS with global convergence. We systematically evaluate the proposed algorithm on three available hyperspectral data sets, and the encouraging experimental results demonstrate the effectiveness of DSML-FS. Numéro de notice : A2015-032 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2321277 En ligne : https://doi.org/10.1109/TGRS.2014.2321277 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75114
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 1 (January 2015) . - pp 261 - 279[article]Réservation
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Titre : Note de géométrie différentielle : L'opérateur Peterson Type de document : Guide/Manuel Auteurs : Abdelmajid Ben Hadj Salem, Auteur Editeur : Tunis [Tunisie] : République tunisienne. Ministère de l’Equipement et de l’Environnement Année de publication : 2015 Autre Editeur : Tunis : Office de la Topographie et de la Cartographie OTC Importance : 9 p. Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Géodésie
[Termes IGN] ellipsoïde de révolution
[Termes IGN] géométrie différentielle
[Termes IGN] matrice
[Termes IGN] sphère
[Termes IGN] théorie des surfacesRésumé : (auteur) L’objet de cette note de géométrie différentielle est l’application d’un théorème de la théorie des surfaces, dit théorème de l’opérateur de Peterson dans les cas de la sphère et de l’ellipsoïde de révolution. Note de contenu : 1. Introduction
2. L'Opérateur de Peterson
3. Applications : Cas de la sphère
3.1. L'expression des dérivées des vecteurs du repère local
3.2. Utilisation du Théorème de l'opérateur de Peterson
4. Calcul des coefficients de la matrice de l'opérateur de PetersonNuméro de notice : 19755 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Manuel de cours Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84555 Documents numériques
en open access
Note de géométrie différentielle - L'opérateur PetersonAdobe Acrobat PDF Generalizations of bounds on the index of convergence to weighted digraphs / Glenn Merlet in Discrete Applied Mathematics, vol 178 ([11/12/2014])
[article]
Titre : Generalizations of bounds on the index of convergence to weighted digraphs Type de document : Article/Communication Auteurs : Glenn Merlet, Auteur ; Thomas Nowak, Auteur ; Hans Schneider, Auteur ; Sergeĭ Sergeev, Auteur Année de publication : 2014 Article en page(s) : pp 121 - 134 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse numérique
[Termes IGN] convergence
[Termes IGN] factorisation de matrice non-négative
[Termes IGN] graphe
[Termes IGN] matrice
[Termes IGN] recherche du chemin optimal, algorithme deIndex. décimale : 23.40 Analyse numérique Résumé : (auteur) We study sequences of optimal walks of a growing length in weighted digraphs, or equivalently, sequences of entries of max-algebraic matrix powers with growing exponents. It is known that these sequences are eventually periodic when the digraphs are strongly connected. The transient of such periodicity depends, in general, both on the size of digraph and on the magnitude of the weights. In this paper, we show that some bounds on the indices of periodicity of (unweighted) digraphs, such as the bounds of Wielandt, Dulmage–Mendelsohn, Schwarz, Kim and Gregory–Kirkland–Pullman, apply to the weights of optimal walks when one of their ends is a critical node. Numéro de notice : A2014-600 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.dam.2014.06.026 En ligne : https://doi.org/10.1016/j.dam.2014.06.026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74894
in Discrete Applied Mathematics > vol 178 [11/12/2014] . - pp 121 - 134[article]Association-matrix-based sample consensus approach for automated registration of terrestrial laser scans using linear features / Kaleel Al-Durgham in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)
[article]
Titre : Association-matrix-based sample consensus approach for automated registration of terrestrial laser scans using linear features Type de document : Article/Communication Auteurs : Kaleel Al-Durgham, Auteur ; Ayman Habib, Auteur Année de publication : 2014 Article en page(s) : pp 1029 - 1039 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] appariement automatique
[Termes IGN] échantillonnage
[Termes IGN] ligne caractéristique
[Termes IGN] matrice
[Termes IGN] Ransac (algorithme)
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) This paper presents an approach for the automatic registration of terrestrial laser scans using linear features. The main contribution here is introducing a new matching strategy that uses an association matrix to store information about candidate matches of linear features. The motivation for this work is aiding the 3D modeling of industrial sites rich with pole-like features. The proposed matching strategy aims at establishing hypotheses about potential minimal watches of linear features that could be used for the estimation of the transformation parameters relating the scans; then, quantifying the agreement between the scans using the estimated transformation parameters. We combine the association matrix and the well-known RANSAC approach for the derivation of conjugate pairs among the two scans. Rather than randomly selecting the line pairs as in the RANSAC-based registration, the association matrix guides the process of selecting the candidate matches of linear features. Experiments are conducted using laser scanning data of an electrical substation to assess the performance of the proposed association-matrix-based sample consensus approach as it compares to the traditional RANSAC-based procedure. The association-matrix-based approach showed consistent tendency of bringing up the correct mutches first before the RANSAC-based registration. Numéro de notice : A2014-615 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.11.1029 En ligne : https://doi.org/10.14358/PERS.80.11.1029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74921
in Photogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 11 (November 2014) . - pp 1029 - 1039[article]Automated hyperspectral vegetation index retrieval from multiple correlation matrices with HyperCor / Helge Aasen in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 8 (August 2014)
[article]
Titre : Automated hyperspectral vegetation index retrieval from multiple correlation matrices with HyperCor Type de document : Article/Communication Auteurs : Helge Aasen, Auteur ; Martin Leon Gnyp, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp. 785 - 795 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] logiciel de corrélation
[Termes IGN] matriceRésumé : (Auteur) Hyperspectral vegetation indices have shown high potential for characterizing, classifying, monitoring, and modeling of vegetation and agricultural crops. Correlation matrices from hyperspectral vegetation indices and plant growth parameters help select important wavelength domains and identify redundant bands.
We introduce the software HyperCor for automated pre-processing of narrowband hyperspectral field data and computation of correlation matrices. In addition, we propose a multi-correlation matrix strategy which combines multiple correlation matrices from different datasets and uses more information from each matrix.
We apply this method to a large multi-temporal spectral li-brary to derive vegetation indices and related regression mod-els for rice biomass detection in the tillering, stem elongation, heading and across all growth stages. The models are cali¬brated with data from three consecutive years and validated with two other years. The results reveal that the multi-corre¬lation matrix strategy can improve the model performance by 10 to 62 percent, depending on the growth stage.Numéro de notice : A2014-346 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.8.745 En ligne : https://doi.org/10.14358/PERS.80.8.745 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73719
in Photogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 8 (August 2014) . - pp. 785 - 795[article]Semisupervised dual-geometric subspace projection for dimensionality reduction of hyperspectral image data / Shuyuan Yang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)PermalinkSpatial and spectral image fusion using sparse matrix factorization / Bo Huang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)PermalinkNonlinear unmixing of hyperspectral data using semi-nonnegative matrix factorization / Naoto Yokoya in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkStructured sparse method for hyperspectral unmixing / Feiyun Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkLa construction d'une matrice de flux à partir de traces de téléphones portables / Françoise Bahoken in Cartes & Géomatique, n° 217 (septembre 2013)PermalinkVisual discovery of synchronisation in weather data at multiple temporal resolutions / Xiaojing Wu in Cartographic journal (the), vol 50 n° 3 (August 2013)PermalinkCombined bundle block adjustment with spaceborne linear array and airborne frame array imagery / Yongjun Zhang in Photogrammetric record, vol 28 n° 142 (June - August 2013)PermalinkManifold regularized sparse NMF for hyperspectral unmixing / Xiaqiang Lu in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)PermalinkPermalinkManual of photogrammetry, sixth edition / J. Chris Mcglone (2013)Permalink