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Robust hyperspectral vision-based classification for multi-season weed mapping / Y. Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)
[article]
Titre : Robust hyperspectral vision-based classification for multi-season weed mapping Type de document : Article/Communication Auteurs : Y. Zhang, Auteur ; D. Slaughter, Auteur ; E. Staab, Auteur Année de publication : 2012 Article en page(s) : pp 65 - 73 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] classification bayesienne
[Termes IGN] cultures
[Termes IGN] herbe
[Termes IGN] identification de plantes
[Termes IGN] image hyperspectrale
[Termes IGN] photogrammétrie métrologique
[Termes IGN] réflectance végétale
[Termes IGN] système expert
[Termes IGN] variation saisonnièreRésumé : (Auteur) This study investigated the robustness of hyperspectral image-based plant recognition to seasonal variability in a natural farming environment in the context of automated in-row weed control. A machine vision system was developed and equipped with a CCD camera integrated with a line-imaging spectrograph for close-range weed sensing and mapping. Three canonical Bayesian classifiers were developed using canopy reflectance (400–795 nm) collected over three seasons for tomato and weeds. The performance of the three season-specific classifiers was tested by changing environmental conditions, resulting in an increase in total error rate of up to 36%. Global calibration across the complete span of the three seasons produced overall classification accuracies of 85.0%, 90.0% and 92.7%, respectively, for 2005, 2006 and 2008. To improve the stability of global classifier over multiple seasons, a multiclassifier system was constructed with three canonical Bayesian classifiers optimized for the three seasons individually. This system was tested on a data set simulating an upcoming season with field conditions similar to that in 2005. The system increased the total discrimination accuracy to 95.8% for the tested season under simulation. This method provided an innovative direction for achieving robust plant recognition over multiple seasons by integrating expert knowledge from historical data that most closely matched the new field environment. Numéro de notice : A2012-194 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.02.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.02.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31641
in ISPRS Journal of photogrammetry and remote sensing > vol 69 (April 2012) . - pp 65 - 73[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012031 SL Revue Centre de documentation Revues en salle Disponible
Titre : 3D visualization of multivariate data Type de document : Thèse/HDR Auteurs : Harald Sanftmann, Auteur ; Daniel Weiskopf, Directeur de thèse ; H. Hauser, Directeur de thèse Editeur : Stuttgart : University of Stuttgart Année de publication : 2012 Importance : 157 p. Format : 21 x 30 cm Note générale : Bibliographie
Von der Fakultät Informatik, Elektrotechnik und Informationstechnik der Universität Stuttgart zur Erlangung der Würde eines Doktors der Naturwissenschaften, genehmigte AbhandlungLangues : Anglais (eng) Descripteur : [Termes IGN] anaglyphe
[Termes IGN] analyse multivariée
[Termes IGN] apprentissage profond
[Termes IGN] arbre de décision
[Termes IGN] éclairement lumineux
[Termes IGN] restitution numérique
[Termes IGN] semis de points
[Termes IGN] traitement de semis de points
[Termes IGN] visualisation 3D
[Vedettes matières IGN] GéovisualisationIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Nowadays large amounts of data are organized in tables, especially in relational databases where the rows store the data items to which multiple attributes are stored in the columns. Information stored this way, having multiple (more than two or three) attributes, can be treated as multivariate data. Therefore, visualization methods for multivariate data have a large application area and high potential utility. This thesis focuses on the application of 3D scatter plots for the visualization of multivariate data. When dealing with 3D, spatial perception needs to be exploited, by effectively using depth cues to convey spatial information to the user. To improve the presentation of individual 3D scatter plots, a technique is presented that applies illumination to them, thus using the shape-from-shading depth cue. To enable the analysis not only of 3D but of multivariate data, a novel technique is introduced that allows the navigation between 3D scatter plots. Inspecting the large number of 3D scatter plots that can be projected from a multivariate data set is very time consuming. The analysis of multivariate data can benefit from automatic machine learning approaches. A presented method uses decision trees to increase the speed a user can gain an understanding of the multivariate data at no extra cost. Stereopsis can also support the display of 3D scatter plots. Here an improved anaglyph rendering technique is presented, significantly reducing ghosting artifacts. The technique is not only applicable for information visualization, but for general rendering or to present stereoscopic image data. Some information visualization algorithms require high computation time. Many of these algorithms can be parallelized to run interactively. A framework that supports the parallelization on shared and distributed memory systems is presented. Note de contenu : Introduction
1 - The Notion of 3D in Information Visualization
2 - Improving Depth Perception of 3D Scatter Plots
3 - 3D Scatter Plot Navigation
4 - Visualization with Decision Trees
5 - Anaglyph Stereo without Ghosting
6 - Distributed Visualization
Conclusion and OutlookNuméro de notice : 21571 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Thèse étrangère Note de thèse : PhD dissertation : Informatik, Elektrotechnik und Informationstechnik : Universität Stuttgart : 2012 DOI : 10.18419/opus-6401 En ligne : http://doi.org/10.18419/opus-6401 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90561 An assessment of internal neural network parameters affecting image classification accuracy / L. Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 12 (December 2011)
[article]
Titre : An assessment of internal neural network parameters affecting image classification accuracy Type de document : Article/Communication Auteurs : L. Zhou, Auteur ; X. Yang, Auteur Année de publication : 2011 Article en page(s) : pp 1233 - 1240 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] image Landsat-ETM+
[Termes IGN] Perceptron multicouche
[Termes IGN] précision de la classification
[Termes IGN] précision des donnéesRésumé : (Auteur) Neural networks are attractive intelligence techniques increasingly being used to classify remote sensor imagery. However, their performance is contingent upon a wide range of algorithm and non-algorithm factors. Despite significant progresses being made over the past two decades, there is no consistent guidance that has been established to automate the use of neural networks in remote sensing. The purpose of this study was to assess several internal parameters affecting image classification accuracy by multi-layer-perceptron (mlp) neural networks. The MLP networks have been considered as the most popular neural network architecture. We carefully configured and trained a set of neural network models with different internal parameter settings. Then, we used these models to classify an Enhanced Thematic Mapper Plus (ETM+) image into several major land cover categories, and the accuracy of each classified map was assessed. The results reveal that number of hidden layers, activation function, and training rate can substantially affect the classification accuracy and that a neural network with appropriate internal parameters can lead to a significant classification accuracy improvement for urban land covers when comparing to the outcome by the Gaussian Maximum Likelihood (GML) classifier. These findings can help design efficient neural network models for improved performance. Numéro de notice : A2011-488 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.77.12.1233 En ligne : https://doi.org/10.14358/PERS.77.12.1233 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31382
in Photogrammetric Engineering & Remote Sensing, PERS > vol 77 n° 12 (December 2011) . - pp 1233 - 1240[article]Object-based image analysis of high-resolution satellite images using modified cloud basis function neural network and probabilistic relaxation labeling process / A. Rizvi in IEEE Transactions on geoscience and remote sensing, vol 49 n° 12 Tome 1 (December 2011)
[article]
Titre : Object-based image analysis of high-resolution satellite images using modified cloud basis function neural network and probabilistic relaxation labeling process Type de document : Article/Communication Auteurs : A. Rizvi, Auteur ; B. Mohan, Auteur Année de publication : 2011 Article en page(s) : pp 4815 - 4820 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal
[Termes IGN] estimation de précision
[Termes IGN] fonction de base radiale
[Termes IGN] image à haute résolution
[Termes IGN] processus stochastique
[Termes IGN] segmentation sémantiqueRésumé : (Auteur) Object-based image analysis is quickly gaining acceptance among remote sensing community, and object-based image classification methods are increasingly being used for classification of land use/cover units from high-resolution satellite images with results closer to human interpretation compared to per-pixel classifiers. The problem of nonlinear separability of classes in a feature space consisting of spectral/spatial/textural features is addressed by kernel-based nonlinear mapping of the feature vectors. This facilitates use of linear discriminant functions for classification as used in artificial neural networks (ANNs). In this paper, performance of a recently introduced kernel called cloud basis function (CBF) is investigated with some modification for classification. The CBF has demonstrated superior performance to the tune of about 4% higher classification accuracy compared to conventional radial basis function used in ANN. The results are further improved by using probabilistic relaxation labeling as a postprocessing step. This paper has potential applications in urban planning and urban studies. Numéro de notice : A2011-479 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2171695 Date de publication en ligne : 22/12/2011 En ligne : https://doi.org/10.1109/TGRS.2011.2171695 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31373
in IEEE Transactions on geoscience and remote sensing > vol 49 n° 12 Tome 1 (December 2011) . - pp 4815 - 4820[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2011121A RAB Revue Centre de documentation En réserve L003 Disponible Development of a modified neural network-based land cover classification system using automated data selector and multiresolution remotely sensed data / S. Khorram in Geocarto international, vol 26 n° 6 (October 2011)
[article]
Titre : Development of a modified neural network-based land cover classification system using automated data selector and multiresolution remotely sensed data Type de document : Article/Communication Auteurs : S. Khorram, Auteur ; H. Yuan, Auteur ; F. Van Der Wiele, Auteur Année de publication : 2011 Article en page(s) : pp 435 - 457 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multirésolution
[Termes IGN] carte de Kohonen
[Termes IGN] classification par réseau neuronal
[Termes IGN] données multicapteurs
[Termes IGN] fusion d'images
[Termes IGN] image Landsat-TM
[Termes IGN] image SPOT
[Termes IGN] occupation du sol
[Termes IGN] Perceptron multicouche
[Termes IGN] précision de la classificationRésumé : (Auteur) Integrating multiple images with artificial neural networks (ANN) improves classification accuracy. ANN performance is sensitive to training datasets. Complexity and errors compound when merging multiple data, pointing to needs for new techniques. Kohonen's self-organizing mapping (KSOM) neural network was adapted as an automated data selector (ADS) to replace manual training data processes. The multilayer perceptron (MLP) network was then trained using automatically extracted datasets and used for classification. Two hypotheses were tested: ADS adapted from the KSOM network provides adequate and reliable training datasets, improving MLP classification performance; and fusion of Landsat Thematic Mapper (TM) and SPOT images using the modified ANN approach increases accuracy. ADS adapted from the KSOM network improved training data quality and increased classification accuracy and efficiency. Fusion of compatible multiple data can improve performance if appropriate training datasets are collected. This proved to be a viable classification scheme particularly where acquiring sufficient and reliable training datasets is difficult. Numéro de notice : A2011-402 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.600462 Date de publication en ligne : 10/08/2011 En ligne : https://doi.org/10.1080/10106049.2011.600462 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31181
in Geocarto international > vol 26 n° 6 (October 2011) . - pp 435 - 457[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2011061 RAB Revue Centre de documentation En réserve L003 Disponible Building agent-based walking models by machine-learning on diverse databases of space-time trajectory samples / Paul M. Torrens in Transactions in GIS, vol 15 supplement s1 (July 2011)PermalinkDétection de bateaux dans les images satellitaires optiques panchromatiques / N. Proia in Revue Française de Photogrammétrie et de Télédétection, n° 194 (Mai 2011)PermalinkApplication des algorithmes génétiques à la recherche de sous-réseaux de stations de télémétrie laser / David Coulot in Bulletin d'information scientifique et technique de l'IGN, n° 77 (avril 2011)PermalinkA genetic programming approach to estimate vegetation cover in the context of soil erosion assessment / C. Puente in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 4 (April 2011)PermalinkIncremental segmentation of lidar point clouds with an octree-structured voxel space / M. Wang in Photogrammetric record, vol 26 n° 133 (March - May 2011)PermalinkA genetic algorithm approach to moving threshold optimization for binary change detection / J. Im in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 2 (February 2011)PermalinkA hybrid classification scheme for mining multisource geospatial data / R. Vatsavai in Geoinformatica, vol 15 n° 1 (January 2011)PermalinkParameterizing support vector machines for land cover classification / X. Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 1 (January 2011)PermalinkPermalinkEqual arc ratio projection and a new spherical triangle quadtree model / Y. Wen in International journal of geographical information science IJGIS, vol 24 n°11-12 (december 2010)PermalinkLocal manifold learning-based k-Nearest-Neighbor for hyperspectral image classification / Li Ma in IEEE Transactions on geoscience and remote sensing, vol 48 n° 11 (November 2010)PermalinkSimilarity 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)PermalinkAutomatic fuzzy clustering using modified differential evolution for image classification / U. Maulik in IEEE Transactions on geoscience and remote sensing, vol 48 n° 9 (September 2010)PermalinkDétection de dommages et évaluation des dégâts du réseau routier après un séisme, en utilisant des images QuickBird haute résolution / A. Haghighattalab in XYZ, n° 124 (septembre - novembre 2010)PermalinkSemisupervised one-class support vector machine for classification of remote sensing data / Jordi Munoz-Mari in IEEE Transactions on geoscience and remote sensing, vol 48 n° 8 (August 2010)PermalinkA volumetric approach to change in satellite images / T. Pollard in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 7 (July 2010)PermalinkSegmentation et interprétation de nuages de points pour la modélisation d'environnements urbains / J. Hernandez in Revue Française de Photogrammétrie et de Télédétection, n° 191 (Mai 2010)PermalinkAutomatic segmentation of Lidar data into coplanar point clusters using an octree-based split-and-merge algorithm / M. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 4 (April 2010)PermalinkUn graphe génératif pour la classification semi-supervisée / P. Gaillard in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 15 n° 2 (mars - avril 2010)PermalinkAutomatic cluster identification for environnemental applications using the self-organizing maps and a new genetic algorithm / T. Oyana in Geocarto international, vol 25 n° 1 (February 2010)PermalinkClassification des tissus urbains à partir de données vectorielles : application à Strasbourg / Anne Puissant (2010)PermalinkPermalinkExtraction of vertical posts in 3D laser point clouds acquired in dense urban areas by a mobile mapping system / Sterenn Liberge (2010)PermalinkGlobal optimization of core station networks for space geodesy: application to the referencing of the SLR EOP with respect to ITRF / David Coulot in Journal of geodesy, vol 84 n° 1 (January 2010)PermalinkSupport vector machines for urban growth modeling / B. Huang in Geoinformatica, vol 14 n° 1 (January 2010)PermalinkUtilising urban context recognition and machine learning to improve the generalisation of buildings / Stefan Steiniger in International journal of geographical information science IJGIS, vol 24 n°1-2 (january 2010)PermalinkAdaptive registration of remote sensing images using supervised learning / L. Eikvil in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 11 (November 2009)PermalinkA matching algorithm for detecting land use changes using case-based reasoning / X. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 11 (November 2009)PermalinkA neural network-based method for solving "nested hierarchy" areal interpolation problems / D. Merwin in Cartography and Geographic Information Science, vol 36 n° 4 (October 2009)PermalinkA data-mining approach for assessing consistency between multiple representations in spatial databases / David Sheeren in International journal of geographical information science IJGIS, vol 23 n° 7-8 (july 2009)PermalinkOptimizing Support Vector Machine learning for semi-arid vegetation mapping by using clustering analysis / L. Su in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 4 (July - August 2009)PermalinkAn adaptive thresholding multiple classifiers system for remote sensing image classification / Y. Tzeng in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 6 (June 2009)PermalinkPotentiality of feed-forward neural networks for classifying dark formations to oil spills and look-alikes / Konstantinos Topouzelis in Geocarto international, vol 24 n° 3 (June - July 2009)PermalinkRepresenting geographical objects with scale-induced indeterminate boundaries: a neural network-based data model / José L. Silvan-Cardenas in International journal of geographical information science IJGIS, vol 23 n°3-4 (march - april 2009)PermalinkPerfectionnement du moteur de rendu 3D des données géographiques de la société Realitymaps / Adrien Chassard (2009)PermalinkPermalinkvol 29 n° 21 - October 2008 - Satellite observations of the atmosphere, oceans and their interface in relation to climate, natural hazards and management of coastal zone (Bulletin de International Journal of Remote Sensing IJRS) / G. LevyPermalinkvol 74 n° 10 - October 2008 - Artificial intelligence in remote sensing (Bulletin de Photogrammetric Engineering & Remote Sensing, PERS) / American society for photogrammetry and remote sensingPermalinkSimulating complex adaptative geographic systems: a geographically aware intelligent agent approach / W. Tang in Cartography and Geographic Information Science, vol 35 n° 4 (October 2008)PermalinkSubpixel urban land cover estimation: comparing cubist, random forests, and support vector regression / J. Walton in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 10 (October 2008)PermalinkEfficient implementation techniques for topological predicates on complex spatial objects / R. Praing in Geoinformatica, vol 12 n° 3 (September - November 2008)PermalinkGeneralization-oriented road line classification by means of an artificial neural network / J.L. Garcia Balboa in Geoinformatica, vol 12 n° 3 (September - November 2008)PermalinkUsing neural networks and cellular automata for modelling intra-urban land-use dynamics / C.M. Almeida in International journal of geographical information science IJGIS, vol 22 n° 8-9 (august 2008)PermalinkA framework of region-based spatial relations for non-overlapping features and its application in object based image analysis / Y. Liu in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 4 (July - August 2008)PermalinkUn algorithme génétique pour le transport à la demande en convergence : application au territoire de la communauté d'agglomération du Pays de Montbéliard / R. Chevrier in Revue internationale de géomatique, vol 18 n° 2 (juin - aout 2008)PermalinkLand-cover change and environmental impact analysis in the Greater Mankato area of Minnesota using remote sensing and GIS modelling / F. Yuan in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)PermalinkThe application of artificial neural networks to the analysis of remotely sensed data / J.F. Mas in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)PermalinkCapture de layers durant une session dans un globe virtuel / G. Mazabraud (2008)PermalinkCSTST 2008, the 5th International conference on soft computing as transdisciplinary science and technology, October 28th - October 31st 2008, University of Cergy-Pontoise, France / Richard Chbeir (2008)PermalinkÉtude comparative de différentes méthodes d'estimation / Samuel Nahmani (2008)PermalinkBorder vector detection and adaptation for classification of multispectral and hyperspectral remote sensing images / N.G. Kasapoglu in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkRévision des connaissances d'un processus de généralisation de données géographiques / Patrick Taillandier in Le monde des cartes, n° 194 (décembre 2007)PermalinkA supervised artificial immune classifier for remote-sensing imagery / Y. Zhong in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkVisibility prediction based on artificial neural networks used in automatic network design / M. Saadatseresht in Photogrammetric record, vol 22 n° 120 (December 2007 - February 2008)PermalinkFeature selection by genetic algorithms in object-based classification of Ikonos imagery for forest mapping in Flanders, Belgium / F.M.B. Van Coillie in Remote sensing of environment, vol 110 n° 4 (30/10/2007)PermalinkArtificial neural network with backpropagation learning to predict mean monthly total ozone in Arosa, Switzerland / S. Chattopadhyay in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkClassified road detection from satellite images based on perceptual organization / J. Yang in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkMultispectral image classification: a supervised neural computation approach based on rough-fuzzy membership function and weak fuzzy similarity relation / A. Agrawal in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkBrainy positioning: processing GPS data with neural networks / Rodrigo Figueiredo Leandro in GPS world, vol 18 n° 9 (September 2007)PermalinkMapping of environmental data using kernel-based methods / Mikhail Kanevski in Revue internationale de géomatique, vol 17 n° 3-4 (septembre 2007 – février 2008)PermalinkWeight-proportional space partitioning using adaptative Voronoi diagrams / R. Reitsma in Geoinformatica, vol 11 n° 3 (September - November 2007)PermalinkMultitemporel fuzzy classification model based on class transition possibilities / G.L.A. Mota in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)PermalinkSpatio-temporal urban landscape change analysis using the Markov chain model and a modified genetic algorithm / J. Tang in International Journal of Remote Sensing IJRS, vol 28 n°15-16 (August 2007)PermalinkAn operational MISR pixel classifier using support vector machines / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkFeature extractions for small sample size classification problem / B.C. Kuo in IEEE Transactions on geoscience and remote sensing, vol 45 n° 3 (March 2007)PermalinkBuilding facade interpretation from uncalibrated wide-baseline image sequences / Helmut Mayer in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 6 (February 2007)Permalink8es rencontres nationales des jeunes chercheurs en intelligence artificielle, RJCIA 2007, 4 - 6 juillet 2007, Grenoble, France / Bruno Zanuttini (2007)PermalinkAcquisition automatique de connaissance de guidage d'un processus de généralisation de données géographiques / Patrick Taillandier (2007)PermalinkOptimisation en traitement du signal et de l'image / Patrick Siarry (2007)PermalinkModelling and detection of geospatial objects using texture motifs / S. Bhagavathy in IEEE Transactions on geoscience and remote sensing, vol 44 n° 12 (December 2006)PermalinkA novel transductive SVM for semisupervised classification of remote-sensing images / Lorenzo Bruzzone in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 2 (November 2006)PermalinkModelling adaptive, spatially aware, and mobile agents: Elk migration in Yellowstone / David A. Bennett in International journal of geographical information science IJGIS, vol 20 n° 9 (october 2006)PermalinkA spatial approach to forest-management optimization: linking GIS and multiple objective genetic algorithms / E.I. Ducheyne in International journal of geographical information science IJGIS, vol 20 n° 8 (september 2006)PermalinkLand-cover mapping in the Brazilian amazon using SPOT-4 Vegetation data and machine learning classification methods / João M.B. Carreiras in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 8 (August 2006)PermalinkA support vector method for anomaly detection in hyperspectral imagery / Amit Banerjee in IEEE Transactions on geoscience and remote sensing, vol 44 n° 8 (August 2006)PermalinkA new method to determine near surface air temperature from satellite observations / Ranjit Singh in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkArtificial neural networks for mapping regional-scale upland vegetation from high spatial resolution imagery / H. Mills in International Journal of Remote Sensing IJRS, vol 27 n° 11 (June 2006)PermalinkSubpixel analysis of Landsat ETM/sup +/ using self-organizing map (SOM) neural networks for urban land cover characterization / S. Lee in IEEE Transactions on geoscience and remote sensing, vol 44 n° 6 (June 2006)PermalinkDetection of ancient settlement mounds: archaeological survey based on the STRM terrain model / B.H. Menze in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 3 (March 2006)PermalinkExamining the use of stored navigation knowledge for neural network based INS/GPS integration / Kai-Wei Chiang in Geomatica, vol 60 n° 1 (March 2006)PermalinkBadly posed classification of remotely sensed images : an experimental comparison of existing data labeling systems / A. Baraldi in IEEE Transactions on geoscience and remote sensing, vol 44 n° 1 (January 2006)PermalinkCAp 2006, 8e conférence francophone sur l'apprentissage automatique, 22 - 24 mai 2006, Trégastel, France / Laurent Miclet (2006)PermalinkCumul de mesures de télémétrie laser sur satellites / Arnaud Pollet (2006)PermalinkPermalinkIntelligence artificielle et jeux / Tristan Cazenave (2006)PermalinkPermalinkPermalinkSdC 2006, Semaine de la connaissance, 26 - 30 juin 2006, Nantes, France, Volume 3. Conférenciers invités, Journées Ontologie et textes juridiques, Indexation des connaissances en sciences humaines / Mounira Harzallah (2006)PermalinkSdC 2006, Semaine de la connaissance, 26 - 30 juin 2006, Nantes, France, Volume 4. Applications industrielles des technologies de la connaisance ; Pratiques et méthodes de classification du savoir à l'heure d'internet ; Récit et gestion des connaissances ; Représentation et raisonnement sur le temps et l'espace / Mounira Harzallah (2006)PermalinkPermalinkIntegrating LIDAR elevation data, multi-spectral imagery and neural network modelling for marsh characterization / J.T. Morris in International Journal of Remote Sensing IJRS, vol 26 n° 23 (December 2005)PermalinkA change detection model based on neighborhood correlation image analysis and decision tree classification / J. Im in Remote sensing of environment, vol 99 n° 3 (30/11/2005)PermalinkAn application of problem and product ontologies for the revision beach nourishments / Daniel van de Vlag in International journal of geographical information science IJGIS, vol 19 n° 10 (november 2005)PermalinkSupervised image classification by contextual adaboost based on posteriors in neighborhoods / Ryuei Nishii in IEEE Transactions on geoscience and remote sensing, vol 43 n° 11 (November 2005)PermalinkAn artificial-neural-network-based, constrained CA model for simulating urban growth / Q. Guan in Cartography and Geographic Information Science, vol 32 n° 4 (October 2005)Permalink