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Fusion of images and point clouds for the semantic segmentation of large-scale 3D scenes based on deep learning / Rui Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 143 (September 2018)
[article]
Titre : Fusion of images and point clouds for the semantic segmentation of large-scale 3D scenes based on deep learning Type de document : Article/Communication Auteurs : Rui Zhang, Auteur ; Guangyun Li, Auteur ; Minglei Li, Auteur ; Li Wang, Auteur Année de publication : 2018 Article en page(s) : pp 85 - 96 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage profond
[Termes IGN] détection du bâti
[Termes IGN] fusion de données
[Termes IGN] réseau neuronal convolutif
[Termes IGN] scène 3D
[Termes IGN] segmentation sémantique
[Termes IGN] semis de pointsRésumé : (Auteur) We address the issue of the semantic segmentation of large-scale 3D scenes by fusing 2D images and 3D point clouds. First, a Deeplab-Vgg16 based Large-Scale and High-Resolution model (DVLSHR) based on deep Visual Geometry Group (VGG16) is successfully created and fine-tuned by training seven deep convolutional neural networks with four benchmark datasets. On the val set in CityScapes, DVLSHR achieves a 74.98% mean Pixel Accuracy (mPA) and a 64.17% mean Intersection over Union (mIoU), and can be adapted to segment the captured images (image resolution 2832 ∗ 4256 pixels). Second, the preliminary segmentation results with 2D images are mapped to 3D point clouds according to the coordinate relationships between the images and the point clouds. Third, based on the mapping results, fine features of buildings are further extracted directly from the 3D point clouds. Our experiments show that the proposed fusion method can segment local and global features efficiently and effectively. Numéro de notice : A2018-356 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.022 Date de publication en ligne : 11/05/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90590
in ISPRS Journal of photogrammetry and remote sensing > vol 143 (September 2018) . - pp 85 - 96[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018091 RAB Livre Centre de documentation En réserve L003 Disponible 081-2018093 DEP-EXM Livre LASTIG Dépôt en unité Exclu du prêt 081-2018092 DEP-EAF Livre Nancy Dépôt en unité Exclu du prêt Incorporating crown shape information for identifying ash tree species / Haijian Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 8 (août 2018)
[article]
Titre : Incorporating crown shape information for identifying ash tree species Type de document : Article/Communication Auteurs : Haijian Liu, Auteur ; Changshan Wu, Auteur Année de publication : 2018 Article en page(s) : pp 495 - 503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Fraxinus (genre)
[Termes IGN] fusion de données
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Milwaukee
[Termes IGN] photo-interprétation assistée par ordinateur
[Termes IGN] zone urbaineRésumé : (Auteur) Identifying ash trees from other common deciduous trees is challenging due to subtle spectral differences of foliage among species. Although many researchers have integrated lidar-derived tree height and crown size metrics to improve tree species classification accuracy, these simple biophysical attributes provide inadequate explanatory power in distinguishing ash trees (Fraxinus, spp.) in urban ecosystems. To address this issue, shape-related features, including crown shape index (SI) and coefficient of variation (CV) of crown height, were extracted from lidar data, and fused with treetopbased spectra for ash tree species identification in Milwaukee City, Wisconsin, United States. Analysis results indicate shape features including SI and CV play a big role in improving the accuracy for ash tree identification. Specifically, Fusion of CV and treetop-based spectra improved the overall accuracy from 81.9 percent to 89 percent, and McNemar tests indicated the differences in accuracy between CV fusion and tree height fusion was statistically significant (p = 0.016). Numéro de notice : A2018-360 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.8.495 Date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.14358/PERS.84.8.495 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90600
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 8 (août 2018) . - pp 495 - 503[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2018081 RAB Revue Centre de documentation En réserve L003 Disponible HackAIR : towards raising awareness about air quality in Europe by developing a collective online platform / Evangelos Kosmidis in ISPRS International journal of geo-information, vol 7 n° 5 (May 2018)
[article]
Titre : HackAIR : towards raising awareness about air quality in Europe by developing a collective online platform Type de document : Article/Communication Auteurs : Evangelos Kosmidis, Auteur ; Panagiota Syropoulou, Auteur ; Stavros Tekes, Auteur ; Philipp Schneider, Auteur ; Eleftherios Spyromitros-Xioufis, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] données environnementales
[Termes IGN] fusion de données
[Termes IGN] image numérique
[Termes IGN] image RVB
[Termes IGN] participation du public
[Termes IGN] pollution atmosphérique
[Termes IGN] qualité de l'air
[Termes IGN] réseau social
[Termes IGN] science citoyenne
[Termes IGN] surveillance écologiqueRésumé : (Auteur) Although air pollution is one of the most significant environmental factors posing a threat to human health worldwide, air quality data are scarce or not easily accessible in most European countries. The current work aims to develop a centralized air quality data hub that enables citizens to contribute to air quality monitoring. In this work, data from official air quality monitoring stations are combined with air pollution estimates from sky-depicting photos and from low-cost sensing devices that citizens build on their own so that citizens receive improved information about the quality of the air they breathe. Additionally, a data fusion algorithm merges air quality information from various sources to provide information in areas where no air quality measurements exist. Numéro de notice : A2018-342 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7050187 Date de publication en ligne : 12/05/2018 En ligne : https://doi.org/10.10.3390/ijgi7050187 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90564
in ISPRS International journal of geo-information > vol 7 n° 5 (May 2018)[article]Combining land cover products using a minimum divergence and a Bayesian data fusion approach / Sarah Gengler in International journal of geographical information science IJGIS, vol 32 n° 3-4 (March - April 2018)
[article]
Titre : Combining land cover products using a minimum divergence and a Bayesian data fusion approach Type de document : Article/Communication Auteurs : Sarah Gengler, Auteur ; Patrick Bogaert, Auteur Année de publication : 2018 Article en page(s) : pp 806 - 826 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] Belgique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification bayesienne
[Termes IGN] distance de Kullback-Leibler
[Termes IGN] entropie maximale
[Termes IGN] entropie relative
[Termes IGN] fusion de données
[Termes IGN] source de donnéesRésumé : (Auteur) Land cover mapping plays an important role for a wide spectrum of applications that are ranging from climate modeling to food security. However, it is a common case that several and partially conflicting land cover products are available at the same time over a same area, where each product suffers from specific limitations and lack of accuracy. In order to take advantage of the best features of each product while at the same time attenuating their respective weaknesses, this paper is proposing a methodology that allows the user to combine these products together based on a general framework involving maximum entropy/minimum divergence principles, Bayesian data fusion and Bayesian updating. First, information brought by each land cover product is coded in terms of inequality constraints so that a first estimation of their quality can be computed based on a maximum entropy/minimum divergence principle. Information from these various land cover products can then be fused afterwards in a Bayesian framework, leading to a single map with an associated measure of uncertainty. Finally, it is shown how the additional information brought by control data can help improving this fused map through a Bayesian updating procedure. The first part of the paper is briefly presenting the most important theoretical results, while the second part is illustrating the use of this suggested approach for a specific area in Belgium, where five different land cover products are at hand. The benefits and limitations of this approach are finally discussed by the light of the results for this case study. Numéro de notice : A2018-045 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1413577 En ligne : https://doi.org/10.1080/13658816.2017.1413577 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89267
in International journal of geographical information science IJGIS > vol 32 n° 3-4 (March - April 2018) . - pp 806 - 826[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018022 RAB Revue Centre de documentation En réserve L003 Disponible 079-2018021 RAB Revue Centre de documentation En réserve L003 Disponible Improving the upscaling of land cover maps by fusing uncertainty and spatial structure information / Peijun Sun in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 2 (February 2018)
[article]
Titre : Improving the upscaling of land cover maps by fusing uncertainty and spatial structure information Type de document : Article/Communication Auteurs : Peijun Sun, Auteur ; Russell G. Congalton, Auteur ; Yaozhong Pan, Auteur Année de publication : 2018 Article en page(s) : pp 87 - 100 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] Caroline du Sud (Etats-Unis)
[Termes IGN] carte agricole
[Termes IGN] carte d'occupation du sol
[Termes IGN] erreur systématique
[Termes IGN] fusion de données
[Termes IGN] incertitude des données
[Termes IGN] Indiana (Etats-Unis)
[Termes IGN] mise à jour de base de donnéesRésumé : (Auteur) Upscaling land cover maps is broadly employed to fill data gaps or match the spatial-resolution of preexisting projects. However, existing methods introduce systematic errors in the area information and the landscape pattern. We developed an upscaling method fusing the spatial structure information (i.e., class Membership probability) and the uncertainty information of the base map (e.g., Confidence level probability), called Fusing class Membership probability and Confidence level probability (FMC). The results showed that FMC obtained higher upscaling efficiency, and mitigated the negative influence of landscape heterogeneity and the negative influence of unequal proportions of land cover in the base maps, on the upscaling compared to Majority Rule Based (MRB) method. Additionally, FMC can reduce the uncertainty/error when these upscaled maps are used as input to Earth observation model (e.g., land cover change). Numéro de notice : A2018-047 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.84.2.87 En ligne : https://doi.org/10.14358/PERS.84.2.87 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89316
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 2 (February 2018) . - pp 87 - 100[article]Réservation
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