Descripteur
Termes IGN > informatique > intelligence artificielle > apprentissage automatique > algorithme d'apprentissage
algorithme d'apprentissage |
Documents disponibles dans cette catégorie (53)
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
Classification and reconstruction from random projections for hyperspectral imagery / W. Li in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)
[article]
Titre : Classification and reconstruction from random projections for hyperspectral imagery Type de document : Article/Communication Auteurs : W. Li, Auteur ; S. Prasad, Auteur ; J. Fowler, Auteur Année de publication : 2013 Article en page(s) : pp 833 - 843 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme d'apprentissage
[Termes IGN] analyse en composantes principales
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] image hyperspectrale
[Termes IGN] reconstruction d'imageRésumé : (Auteur) There is increasing interest in dimensionality reduction through random projections due in part to the emerging paradigm of compressed sensing. It is anticipated that signal acquisition with random projections will decrease signal-sensing costs significantly; moreover, it has been demonstrated that both supervised and unsupervised statistical learning algorithms work reliably within randomly projected subspaces. Capitalizing on this latter development, several class-dependent strategies are proposed for the reconstruction of hyperspectral imagery from random projections. In this approach, each hyperspectral pixel is first classified into one of several pixel groups using either a conventional supervised classifier or an unsupervised clustering algorithm. After the grouping procedure, a suitable reconstruction method, such as compressive projection principal component analysis, is employed independently within each group. Experimental results confirm that such class-dependent reconstruction, which employs statistics pertinent to each class as opposed to the global statistics estimated over the entire data set, results in more accurate reconstructions of hyperspectral pixels from random projections. Numéro de notice : A2013-082 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2204759 En ligne : https://doi.org/10.1109/TGRS.2012.2204759 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32220
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 2 (February 2013) . - pp 833 - 843[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013021 RAB Revue Centre de documentation En réserve L003 Disponible Triangular factorization-based simplex algorithms for hyperspectral unmixing / W. Xia in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)
[article]
Titre : Triangular factorization-based simplex algorithms for hyperspectral unmixing Type de document : Article/Communication Auteurs : W. Xia, Auteur ; H. Pu, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 4420 - 4440 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme d'apprentissage
[Termes IGN] algorithme du simplexe
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] factorisation
[Termes IGN] image hyperspectrale
[Termes IGN] programmation linéaireRésumé : (Auteur) In the linear unmixing of hyperspectral images, the observation pixels form a simplex whose vertices correspond to the endmembers, hence finding the endmembers is equivalent to extracting these vertices. A common technique for determining vertices is to analyze the simplex volume, but it usually has a high computational complexity, resulting from the exhaustive searching of volume in the large hyperspectral data. This problem limits the practicability and real-time application. In this paper, we utilize triangular factorization (TF) to calculate the volume, deducing a method named simplex volume analysis based on TF (SVATF). It requires just one comparison through the data to succeed in finding the global optimal solution for all the endmembers, thus improving the searching efficiency. Dimensionality reduction transformation is not necessary, which is another advantage of this method. Moreover, since TF is a broad conception including different methods, SVATF is a framework including various implementations. Based on TF, we also propose a fast learning algorithm named abundance quantification based on TF to estimate the abundances, which further saves the computation by utilizing the intermediate values involved in SVATF. The abundance estimation method can rectify possible errors in the given endmembers by utilizing two important constraints (abundance nonnegative constraint and abundance sum-to-one constraint) of the linear mixture model, so it is useful for the imagery without pure pixels. Experimental results on synthetic and real hyperspectral data demonstrate that the proposed methods can obtain accurate results with much lower computational complexity, with respect to other state-of-the-art methods. Numéro de notice : A2012-587 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2195185 Date de publication en ligne : 22/05/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2195185 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32033
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4420 - 4440[article]Verification of 2D building outlines using oblique airborne images / A. Nyaruhuma in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
[article]
Titre : Verification of 2D building outlines using oblique airborne images Type de document : Article/Communication Auteurs : A. Nyaruhuma, Auteur ; Markus Gerke, Auteur ; M. George Vosselman, Auteur ; E.G. Mtalo, Auteur Année de publication : 2012 Article en page(s) : pp 62 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] arbre aléatoire
[Termes IGN] base de données foncières
[Termes IGN] bâtiment
[Termes IGN] boosting adapté
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] contour
[Termes IGN] image aérienne oblique
[Termes IGN] logique floueRésumé : (Auteur) Oblique airborne images are interesting not only for visualization but also for the acquisition and updating of geo-spatial vector data. This is because side views of vertical structures, such as buildings, are present in those images. In recent years, techniques for automatic verification of building outlines have been proposed. These techniques utilized color, texture and height from vertical images or range data while oblique images contain façade information that can also be used to identify buildings. This paper presents a methodology to verify 2D building outlines in a cadastral dataset by using oblique airborne images. The method searches for clues such as building edges, wall façade edges and texture. The 2D clues in images taken from different perspectives but expected to contain the same wall are transformed to 3D, combined and used for a verification of the particular wall. Unlike methods that use vertical images or LIDAR, walls are verified individually and then the results are combined for the building. We compare three methods for combining wall-based evidence. Experiments using almost 700 buildings show that best results are obtained using Adaptive Boosting where – with a bias for better identification of demolished buildings – 100% of demolished buildings are identified and 91% of existing buildings are confirmed. The other two methods are Random Trees and a variant of the Dempster–Shafer approach combined with fuzzy reasoning and they only show some minor differences to the Adaptive Boosting result. The research as presented in this paper demonstrates the potential of oblique images, but some further work has to be done, including the identification of modified buildings and the extension towards verification of 3D building models. Numéro de notice : A2012-348 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.04.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31794
in ISPRS Journal of photogrammetry and remote sensing > vol 71 (July 2012) . - pp 62 - 75[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 081-2012051 SL Revue Centre de documentation Revues en salle Disponible Similarity weighted instance-based learning for the generation of transition potentials in land use change modeling / F. Sangermano in Transactions in GIS, vol 14 n° 5 (October 2010)
[article]
Titre : Similarity weighted instance-based learning for the generation of transition potentials in land use change modeling Type de document : Article/Communication Auteurs : F. Sangermano, Auteur ; J. Ronald Eastman, Auteur ; H. Zhu, Auteur Année de publication : 2010 Article en page(s) : pp 569 - 580 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] algorithme d'apprentissage
[Termes IGN] analyse comparative
[Termes IGN] apprentissage automatique
[Termes IGN] classification barycentrique
[Termes IGN] déboisement
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] Perceptron multicouche
[Termes IGN] similitude
[Termes IGN] traitement de données localisées
[Termes IGN] utilisation du solRésumé : (Auteur) Land use change models are increasingly being used to evaluate the effect of land change on climate and biodiversity and to generate scenarios of deforestation. Although many methods are available to model land transition potentials, they are usually not user-friendly and require the specification of many parameters, making the task difficult for decision makers not familiar with the tools, as well as making the process difficult to interpret. In this article we propose a simple method for modeling transition potentials. SimWeight is an instance-based learning algorithm based on the logic of the K-Nearest Neighbor algorithm. The method identifies the relevance of each driver variable and predicts the transition potential of locations given known instances of change. A case study was used to demonstrate and validate the method. Comparison of results with the Multi-Layer Perceptron neural network (MLP) suggests that SimWeight performs similarly in its capacity to predict transition potentials, without the need for complex parameters. Another advantage of SimWeight is that it is amenable to parallelization for deployment on a cloud computing platform. Numéro de notice : A2010-496 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2010.01226.x Date de publication en ligne : 23/11/2010 En ligne : https://doi.org/10.1111/j.1467-9671.2010.01226.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30689
in Transactions in GIS > vol 14 n° 5 (October 2010) . - pp 569 - 580[article]An adaptive thresholding multiple classifiers system for remote sensing image classification / Y. Tzeng in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 6 (June 2009)
[article]
Titre : An adaptive thresholding multiple classifiers system for remote sensing image classification Type de document : Article/Communication Auteurs : Y. Tzeng, Auteur ; K. Fan, Auteur ; K.S. Chen, Auteur Année de publication : 2009 Article en page(s) : pp 679 - 687 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] classificateur
[Termes IGN] classification automatique
[Termes IGN] classification hybride
[Termes IGN] ensachage
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] seuillage d'imageRésumé : (Auteur) A multiple classifiers system which adopts an effective weighting policy to combine the output of several classifiers, generally leads to a better performance in image classification. The two most commonly used weighting policies are Bagging and Boosting algorithms. However, their performance is limited by high levels of ambiguity among classes. To overcome this difficulty, an adaptive thresholding criterion was proposed. By applying it to SAR and optical images for terrain cover classification, comparisons between the multiple classifiers systems using the Bagging and/or Boosting algorithms with and without the adaptive thresholding criterion were made. Experimental results showed that the classification substantially improved when the adaptive thresholding criterion was used, especially when the level of ambiguity of targets was high. Copyright ASPRS Numéro de notice : A2009-260 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.6.679 En ligne : https://doi.org/10.14358/PERS.75.6.679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29890
in Photogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 6 (June 2009) . - pp 679 - 687[article]Cartographic generalization of roads in a local and adaptive approach: A knowledge acquistion problem / Sébastien Mustière in International journal of geographical information science IJGIS, vol 19 n° 8 - 9 (september 2005)PermalinkNouvelle approche du réseau ARTMAP flou : application à la classification multi-spectrale des images SPOT XS de la baie d'Alger / F. Alilat in Revue Française de Photogrammétrie et de Télédétection, n° 177 (Juin 2005)PermalinkExtraction, par apprentissage supervisé, de textures sur cartes géographiques / Robert Mariani in Bulletin d'information de l'Institut géographique national, n° 68 (octobre 1997)Permalink