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Multi-view urban scene classification with a complementary-information learning model / Wanxuan Geng in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 1 (January 2022)
[article]
Titre : Multi-view urban scene classification with a complementary-information learning model Type de document : Article/Communication Auteurs : Wanxuan Geng, Auteur ; Weixun Zhou, Auteur ; Shuanggen Jin, Auteur Année de publication : 2022 Article en page(s) : pp 65 - 72 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données de terrain
[Termes IGN] données multisources
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion de données multisource
[Termes IGN] image aérienne
[Termes IGN] niveau du sol
[Termes IGN] précision de la classification
[Termes IGN] scène urbaineRésumé : (Auteur) Traditional urban scene-classification approaches focus on images taken either by satellite or in aerial view. Although single-view images are able to achieve satisfactory results for scene classification in most situations, the complementary information provided by other image views is needed to further improve performance. Therefore, we present a complementary information-learning model (CILM) to perform multi-view scene classification of aerial and ground-level images. Specifically, the proposed CILM takes aerial and ground-level image pairs as input to learn view-specific features for later fusion to integrate the complementary information. To train CILM, a unified loss consisting of cross entropy and contrastive losses is exploited to force the network to be more robust. Once CILM is trained, the features of each view are extracted via the two proposed feature-extraction scenarios and then fused to train the support vector machine classifier for classification. The experimental results on two publicly available benchmark data sets demonstrate that CILM achieves remarkable performance, indicating that it is an effective model for learning complementary information and thus improving urban scene classification. Numéro de notice : A2022-063 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00062R2 Date de publication en ligne : 01/01/2022 En ligne : https://doi.org/10.14358/PERS.21-00062R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99708
in Photogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 1 (January 2022) . - pp 65 - 72[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2022011 SL Revue Centre de documentation Revues en salle Disponible A new method for the attribution of breakpoints in segmentation of IWV difference time series / Khanh Ninh Nguyen (2022)
Titre : A new method for the attribution of breakpoints in segmentation of IWV difference time series Type de document : Article/Communication Auteurs : Khanh Ninh Nguyen, Auteur ; Olivier Bock , Auteur ; Emilie Lebarbier, Auteur Editeur : Munich [Allemagne] : European Geosciences Union EGU Année de publication : 2022 Conférence : EGU 2022, General Assembly 23/05/2022 27/05/2022 Vienne Autriche OA Abstracts only Importance : 1 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] données GNSS
[Termes IGN] points de rupture
[Termes IGN] segmentation
[Termes IGN] série temporelle
[Termes IGN] teneur intégrée en vapeur d'eauRésumé : (auteur) In recent years, the detection and correction of the non-natural irregularities in the long climatic records, so-called homogenization, has been studied. This work is motivated by the problem of identification of origins of the breakpoints in the segmentation of difference series (difference between a candidate series and a reference series). Several segmentation methods have been developed for the difference series, but many of them assume that the reference series is homogenous. However, the homogeneity of the reference series, in reality, is uncertain and unproven. In our study, we applied the segmentation method GNSSseg (Quarello et al., 2020) on the difference between the Integrated water vapour estimates of the CODE REPRO2015 GNSS data set and the ERA5 reanalysis. About 36.5% of change points can be validated from the GPS metadata, and the origins of the remaining 64.5% are questionable (Nguyen et al., 2021). The ambiguity can be leveraged when there is at least one nearby GPS station with respect to which the candidate series can be compared. The proposed method uses weighted t-tests combining the candidate GPS and ERA series and their homologues (denoted GPS' and ERA') from each nearby station. If sufficient consistency emerges from the six tests for all the nearby stations, a decision can be made whether the breakpoint detected in the candidate GPS-ERA series is due to GPS or, alternatively, to ERA. For each quadruplet (GPS, ERA, GPS', ERA'), six t-tests are performed, and the outcomes are combined. In a set of 81 globally distributed GNSS time series spanning more than 25 years, 56 series have at least one nearby station, where 171 breakpoints are detected in segmentation, in which 136 breakpoints are attributed to the GPS. Among those, 94 breakpoints have consistent results between all the nearby stations. GPS-related breakpoints are used for the correction of the mean shift in the difference series. The impact of the breakpoint correction on the GNSS IWV trend estimates is then evaluated. Numéro de notice : C2022-009 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : 10.5194/egusphere-egu22-6390 En ligne : https://doi.org/10.5194/egusphere-egu22-6390 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100713 Novel fuzzy clustering algorithm with variable multi-pixel fitting spatial information for image segmentation / Hang Zhang in Pattern recognition, vol 121 (January 2022)
[article]
Titre : Novel fuzzy clustering algorithm with variable multi-pixel fitting spatial information for image segmentation Type de document : Article/Communication Auteurs : Hang Zhang, Auteur ; Haili Li, Auteur ; Ning Chen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 108201 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] classification floue
[Termes IGN] classification pixellaire
[Termes IGN] filtre
[Termes IGN] segmentation d'image
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) Spatial information is often used to enhance the robustness of traditional fuzzy c-means (FCM) clustering algorithms. Although some recently emerged improvements are remarkable, the computational complexity of these algorithms is high, which may lead to lack of practicability. To address this problem, an efficient variant named the fuzzy clustering algorithm with variable multi-pixel fitting spatial information (FCM-VMF) is presented. First, a fuzzy clustering algorithm with multi-pixel fitting spatial information (FCM-MF) is developed. Specifically, by dividing the input image into several filter windows, the spatial information of all pixels in each filter window can be obtained simultaneously by fitting the pixels in its corresponding neighbourhood window, which enormously reduces the computational complexity. However, the FCM-MF may result in the loss of edge information. Therefore, the FCM-VMF integrates a variable window strategy with FCM-MF. In this strategy, to preserve more edge information, the sizes of the filter window and generalized neighbourhood window are adaptively reduced. The experimental results show that FCM-VMF is as effective as some recent algorithms. Notably, the FCM-VMF has extremely high efficiency, which means it has a better prospect of application. Numéro de notice : A2022-100 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.patcog.2021.108201 Date de publication en ligne : 26/07/2021 En ligne : https://doi.org/10.1016/j.patcog.2021.108201 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99564
in Pattern recognition > vol 121 (January 2022) . - n° 108201[article]A novel unmixing-based hypersharpening method via convolutional neural network / Xiaochen Lu in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)
[article]
Titre : A novel unmixing-based hypersharpening method via convolutional neural network Type de document : Article/Communication Auteurs : Xiaochen Lu, Auteur ; Tong Li, Auteur ; Junping Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 5503614 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] pouvoir de résolution spectraleRésumé : (auteur) Hypersharpening (namely, hyperspectral (HS) and multispectral (MS) image fusion) aims at enhancing the spatial resolution of HS image via an auxiliary higher resolution MS image. Currently, numerous hypersharpening methods are proposed successively, among which the unmixing-based approaches have been widely researched and demonstrated their effectiveness in the spectral fidelity aspect. However, existing unmixing-based fusion methods substantially employ mathematical techniques to solve the spectral mixture model, without taking full advantage of the collaborative spatial–spectral information that is usually helpful for abundance estimation improvement. To overcome this drawback, in this article, a novel unmixing-based HS and MS image fusion method, via a convolutional neural network (CNN), is proposed to promote spectral fidelity. The main idea of this work is to use CNN to fully explore the spatial information and the spectral information of both HS and MS images simultaneously, thereby enhancing the accuracy of estimating the abundance maps. Experiments on four simulated and real remote sensing data sets demonstrate that the proposed method is beneficial to the spectral fidelity of the fused images compared with some state-of-the-art algorithms. Meanwhile, it is also easy to implement and has a certain advantage in running time. Numéro de notice : A2022-028 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3063105 Date de publication en ligne : 22/03/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3063105 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99264
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 1 (January 2022) . - n° 5503614[article]Numérique versus symbolique : dialogue ontologique entre deux approches / Hélène Mathian in Revue internationale de géomatique, vol 31 n° 1-2 (janvier - juin 2022)
[article]
Titre : Numérique versus symbolique : dialogue ontologique entre deux approches Type de document : Article/Communication Auteurs : Hélène Mathian, Auteur ; Léna Sanders, Auteur Année de publication : 2022 Article en page(s) : pp 21 - 45 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse comparative
[Termes IGN] analyse de données
[Termes IGN] cadre conceptuel
[Termes IGN] établissement d'enseignement
[Termes IGN] Ile-de-France
[Termes IGN] ontologie
[Termes IGN] simulation dynamique
[Termes IGN] système multi-agentsRésumé : (Auteur) L’objectif de cet article est de comparer une approche statistique, l’analyse des données (AD) et une approche de simulation, les systèmes multi-agents (SMA). Ces deux familles de méthodes sont a priori considérées comme représentatives d’une approche numérique, respectivement symbolique, de la modélisation spatiale. Le cas d’application qui est mobilisé tout au long de l’article est celui de la ségrégation de l’espace scolaire en Île-de-France. En premier lieu sont explicitées et discutées les différentes étapes menant d’une question thématique à l’opérationnalisation d’une méthodologie d’analyse statistique ou de simulation destinée à analyser cette question. Pour effectuer cette comparaison, on développe un cadre conceptuel à l’interface entre les deux, qui permet de vérifier la compatibilité entre les arrières plans théoriques associés aux domaines thématiques et de modélisation en jeu. Ce cadre conceptuel prend appui sur une démarche ontologique qui est ensuite présentée. Celle-ci permet d’identifier les complémentarités entre AD et SMA et de montrer comment ces deux méthodes peuvent dialoguer dans le cadre d’une même recherche. Nous montrons combien les aspects numériques et symboliques sont finalement étroitement imbriqués au sein même de chacune de ces méthodes. Cette imbrication permet de construire une « spirale d’interactions » entre les deux familles de méthodes dont l’intérêt est illustré par les va et vient entre les phases d’analyse de structure et de simulation dynamique dans le cas de la ségrégation scolaire. Numéro de notice : A2022-807 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.3166/rig31.21-45 Date de publication en ligne : 06/12/2022 En ligne : https://doi.org/10.3166/rig31.21-45 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102219
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