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Bayesian transfer learning for object detection in optical remote sensing images / Changsheng Zhou in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 11 (November 2020) . - pp 7705 - 7719 Titre : Bayesian transfer learning for object detection in optical remote sensing images Type de document : Article/Communication Auteurs : Changsheng Zhou, Auteur ; Jiangshe Zhang, Auteur ; Junmin Liu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 7705 - 7719 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] distribution de Fisher [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] théorème de Bayes Résumé : (auteur) In the literature of object detection in optical remote sensing images, a popular pipeline is first modifying an off-the-shelf deep neural network, then initializing the modified network by pretrained weights on a source data set, and finally fine-tuning the network on a target data set. The procedure works well in practice but might not make full use of underlying knowledge implied by pretrained weights. In this article, we propose a novel method, referred to as Fisher regularization, for efficient knowledge transferring. Based on Bayes’ theorem, the method stores underlying knowledge into a Fisher information matrix and fine-tunes parameters based on the knowledge. The proposed method would not introduce extra parameters and is less sensitive to hyperparameters than classical weight decay. Experiments on NWPUVHR-10 and DOTA data sets show that the proposed method is effective and works well with different object detectors. Numéro de notice : A2020-679 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2983201 date de publication en ligne : 14/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2983201 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96182 [article]

Advancing the theory and practice of system evaluation: a case study in geovisual analytics of social media / Alexander Savelyev in International journal of cartography, Vol 6 n° 2 (July 2020)  

Public [article]  inInternational journal of cartography > Vol 6 n° 2 (July 2020) . - pp 202 - 221 Titre : Advancing the theory and practice of system evaluation: a case study in geovisual analytics of social media Type de document : Article/Communication Auteurs : Alexander Savelyev, Auteur ; Alan M. MacEachren, Auteur Année de publication : 2020 Article en page(s) : pp 202 - 221 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse géovisuelle [Termes descripteurs IGN] approche participative [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] logiciel de visualisation [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] utilisateur [Vedettes matières IGN] Géovisualisation Résumé : (auteur) This paper advances the state-of-the-art in methodology design for empirical evaluation of (geo)visual analytics software. Specifically, we describe the process of design, development and application of a prototypical user study tailored to the evaluation of complex geovisual analytics tools that focus on social media analysis. We fist perform a synthesis of existing theory and best practices for software evaluation of comparable systems. We then demonstrate how the product of said synthesis – a methodological ‘check list’ – can be used to inform a proof-of-concept user study of an actual geovisual analytics software system. The resulting user study design accommodates for the use of real geographic social media datasets, the complexity of the intended analytical process, and for the learning challenges faced by the participants working with a fully-functional and mature geovisual analytics application, and is likely representative of a wide range of evaluation scenarios in (geo)visual analytics. A complete summary of all the study instruments is included to encourage their scrutiny, reuse and modification by others. Finally, we have discovered that participants’ curiosity and desire for autonomy played a noticeable role in the evaluation process – something not previously reported. Numéro de notice : A2020-373 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2019.1637488 date de publication en ligne : 01/08/2019 En ligne : https://doi.org/10.1080/23729333.2019.1637488 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95305 [article]

A review of techniques for 3D reconstruction of indoor environments / Zhizhong Kang in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - 31 p. Titre : A review of techniques for 3D reconstruction of indoor environments Type de document : Article/Communication Auteurs : Zhizhong Kang, Auteur ; Juntao Yang, Auteur ; Zhou Yang, Auteur ; Sai Cheng, Auteur Année de publication : 2020 Article en page(s) : 31 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] espace intérieur [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] indoorGML [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] modèle géométrique [Termes descripteurs IGN] modèle sémantique de données [Termes descripteurs IGN] modèle topologique de données [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] Simultaneous Localisation And Mapping Résumé : (auteur) Indoor environment model reconstruction has emerged as a significant and challenging task in terms of the provision of a semantically rich and geometrically accurate indoor model. Recently, there has been an increasing amount of research related to indoor environment reconstruction. Therefore, this paper reviews the state-of-the-art techniques for the three-dimensional (3D) reconstruction of indoor environments. First, some of the available benchmark datasets for 3D reconstruction of indoor environments are described and discussed. Then, data collection of 3D indoor spaces is briefly summarized. Furthermore, an overview of the geometric, semantic, and topological reconstruction of the indoor environment is presented, where the existing methodologies, advantages, and disadvantages of these three reconstruction types are analyzed and summarized. Finally, future research directions, including technique challenges and trends, are discussed for the purpose of promoting future research interest. It can be concluded that most of the existing indoor environment reconstruction methods are based on the strong Manhattan assumption, which may not be true in a real indoor environment, hence limiting the effectiveness and robustness of existing indoor environment reconstruction methods. Moreover, based on the hierarchical pyramid structures and the learnable parameters of deep-learning architectures, multi-task collaborative schemes to share parameters and to jointly optimize each other using redundant and complementary information from different perspectives show their potential for the 3D reconstruction of indoor environments. Furthermore, indoor–outdoor space seamless integration to achieve a full representation of both interior and exterior buildings is also heavily in demand. Numéro de notice : A2020-299 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050330 date de publication en ligne : 19/05/2020 En ligne : https://doi.org/10.3390/ijgi9050330 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95139 [article]

GIS-based modeling for selection of dam sites in the Kurdistan region, Iraq / Arsalan Ahmed Othman in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 34 p. Titre : GIS-based modeling for selection of dam sites in the Kurdistan region, Iraq Type de document : Article/Communication Auteurs : Arsalan Ahmed Othman, Auteur ; Ahmed F. Al-Maamar, Auteur ; Diary Ali Mohammed Amin Al-Manmi, Auteur Année de publication : 2020 Article en page(s) : 34 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] barrage [Termes descripteurs IGN] capacité de stockage [Termes descripteurs IGN] construction [Termes descripteurs IGN] gestion de l'eau [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image Landsat-OLI [Termes descripteurs IGN] image Quickbird [Termes descripteurs IGN] Iraq [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] processus d'analyse hiérarchisée floue [Termes descripteurs IGN] régression géographiquement pondérée Résumé : (auteur) Iraq, a country in the Middle East, has suffered severe drought events in the past two decades due to a significant decrease in annual precipitation. Water storage by building dams can mitigate drought impacts and assure water supply. This study was designed to identify suitable sites to build new dams within the Al-Khabur River Basin (KhRB). Both the fuzzy analytic hierarchy process (AHP) and the weighted sum method (WSM) were used and compared to select suitable dam sites. A total of 14 layers were used as input dataset (i.e., lithology, tectonic zones, distance to active faults, distance to lineaments, soil type, land cover, hypsometry, slope gradient, average precipitation, stream width, Curve Number Grid, distance to major roads, distance to towns and cities, and distance to villages). Landsat-8/Operational Land Imager (OLI) and QuickBird optical images were used in the study. Three types of accuracies were tested: overall, suitable pixels by number, and suitable pixels by weight. Based on these criteria, we determined that 11 sites are suitable for locating dams for runoff harvesting. Results were compared to the location of 21 preselected dams proposed by the Ministry of Agricultural and Water Resources (MAWR). Three of these dam sites coincide with those proposed by the MAWR. The overall accuracies of the 11 dams ranged between 76.2% and 91.8%. The two most suitable dam sites are located in the center of the study area, with favorable geology, adequate storage capacity, and in close proximity to the population centers. Of the two selection methods, the AHP method performed better as its overall accuracy is greater than that of the WSM. We argue that when stream discharge data are not available, use of high spatial resolution QuickBird imageries to determine stream width for discharge estimation is acceptable and can be used for preliminary dam site selection. The study offers a valuable and relatively inexpensive tool to decision-makers for eliminating sites having severe limitations (less suitable sites) and focusing on those with the least restriction (more suitable sites) for dam construction. Numéro de notice : A2020-265 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040244 date de publication en ligne : 15/04/2020 En ligne : https://doi.org/10.3390/ijgi9040244 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95028 [article]

Extracting urban landmarks from geographical datasets using a random forests classifier / Yue Lin in International journal of geographical information science IJGIS, vol 33 n°12 (December 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 33 n°12 (December 2019) . - pp 2406 - 2423 Titre : Extracting urban landmarks from geographical datasets using a random forests classifier Type de document : Article/Communication Auteurs : Yue Lin, Auteur ; Yuyang Cai, Auteur ; Yue Gong, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 2406 - 2423 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] extraction automatique [Termes descripteurs IGN] gestion des itinéraires [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] point de repère [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] représentation mentale spatiale [Termes descripteurs IGN] saillance [Termes descripteurs IGN] Shenzhen [Termes descripteurs IGN] ville Résumé : (auteur) Urban landmarks are of significant importance to spatial cognition and route navigation. However, the current landmark extraction methods mainly focus on the visual salience of landmarks and are insufficient for obtaining high extraction accuracy when the size of the geographical dataset varies. This study introduces a random forests (RF) classifier combining with the synthetic minority oversampling technique (SMOTE) in urban landmark extraction. Both GIS and social sensing data are employed to quantify the structural and cognitive salience of the examined urban features, which are available from basic spatial databases or mainstream web service application programming interfaces (APIs). The results show that the SMOTE-RF model performs well in urban landmark extraction, with the values of recall, precision, F-measure and AUC reaching 0.851, 0.831, 0.841 and 0.841, respectively. Additionally, this method is suitable for both large and small geographical datasets. The ranking of variable importance given by this model further indicates that certain cognitive measures – such as feature class, Weibo popularity and Bing popularity – can serve as crucial factors for determining a landmark. The optimal variable combination for landmark extraction is also acquired, which might provide support for eliminating the variable selection requirement in other landmark extraction methods. Numéro de notice : A2019-426 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1620238 date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1080/13658816.2019.1620238 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93559 [article]

An approach for establishing correspondence between OpenStreetMap and reference datasets for land use and land cover mapping / Qi Zhou in Transactions in GIS, Vol 23 n° 6 (November 2019)  

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PPD: Pyramid Patch Descriptor via convolutional neural network / Jie Wan in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 9 (September 2019)  

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Semantic understanding of scenes through the ADE20K dataset / Bolei Zhou in International journal of computer vision, vol 127 n° 3 (March 2019)  

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Surface reconstruction of incomplete datasets: A novel Poisson surface approach based on CSRBF / Jules Morel in Computers and graphics, vol 74 (August 2018)  

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Assessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets / Ming Li in Geoinformatica [en ligne], vol 22 n° 3 (July 2018)  

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Un modèle pour l’intégration spatiale et temporelle de données géolocalisées / Helbert Arenas in Revue internationale de géomatique, vol 28 n° 2 (avril - juin 2018)  

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A novel orthoimage mosaic method using a weighted A∗ algorithm : Implementation and evaluation / Maoteng Zheng in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

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Géomatique et enseignement secondaire / Cyrille Chopin in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 22 n° 5 (septembre - octobre 2017)

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A GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data / Guiming Zhang in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)  

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A viewpoint based approach to the visual exploration of trajectory / Jie Li in Journal of Visual Languages and Computing, vol 41 (August 2017)  

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