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A novel deep learning instance segmentation model for automated marine oil spill detection / Shamsudeen Temitope Yekeen in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)
[article]
Titre : A novel deep learning instance segmentation model for automated marine oil spill detection Type de document : Article/Communication Auteurs : Shamsudeen Temitope Yekeen, Auteur ; Abdul‐Lateef Balogun, Auteur ; Khamaruzaman B. Wan Yusof, Auteur Année de publication : 2020 Article en page(s) : pp 190 - 200 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] hydrocarbure
[Termes IGN] image radar moirée
[Termes IGN] marée noire
[Termes IGN] segmentation sémantique
[Termes IGN] vision par ordinateur
[Termes IGN] zone d'intérêtRésumé : (auteur) The visual similarity of oil slick and other elements, known as look-alike, affects the reliability of synthetic aperture radar (SAR) images for marine oil spill detection. So far, detection and discrimination of oil spill and look-alike are still limited to the use of traditional machine learning algorithms and semantic segmentation deep learning models with limited accuracy. Thus, this study developed a novel deep learning oil spill detection model using computer vision instance segmentation Mask-Region-based Convolutional Neural Network (Mask R-CNN) model. The model training was conducted using transfer learning on the ResNet 101 on COCO as backbone in combination with Feature Pyramid Network (FPN) architecture for feature extraction at 30 epochs with 0.001 learning rate. Testing of the model was conducted using the least training and validation loss value on the withheld testing images. The model’s performance was evaluated using precision, recall, specificity, IoU, F1-measure and overall accuracy values. Ship detection and segmentation had the highest performance with overall accuracy of 98.3%. The model equally showed a higher accuracy for oil spill and look-alike detection and segmentation although oil spill detection outperformed look-alike with overall accuracy values of 96.6% and 91.0% respectively. The study concluded that the deep learning instance segmentation model performs better than conventional machine learning models and deep learning semantic segmentation models in detection and segmentation. Numéro de notice : A2020-548 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.07.011 Date de publication en ligne : 28/07/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.07.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95774
in ISPRS Journal of photogrammetry and remote sensing > vol 167 (September 2020) . - pp 190 - 200[article]Réservation
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[article]
Titre : A novel deep network and aggregation model for saliency detection Type de document : Article/Communication Auteurs : Ye Liang, Auteur ; Hongzhe Liu, Auteur ; Nan Ma, Auteur Année de publication : 2020 Article en page(s) : pp 1883 - 1895 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage profond
[Termes IGN] architecture de réseau
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] déconvolution
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] saillanceRésumé : (auteur) Recent deep learning-based methods for saliency detection have proved the effectiveness of integrating features with different scales. They usually design various complex architectures of network, e.g., multiple networks, to explore the multi-scale information of images, which is expensive in computation and memory. Feature maps produced with different subsampling convolutional layers have different spatial resolutions; therefore, they can be used as the multi-scale features to reduce the costs. In this paper, by exploiting the in-network feature hierarchy of convolutional networks, we propose a novel multi-scale network for saliency detection (MSNSD) consisting of three modules, i.e., bottom-up feature extraction, top-down feature connection and multi-scale saliency prediction. Moreover, to further boost the performance of MSNSD, an input image-aware saliency aggregation method is proposed based on the ridge regression, which combines MSNSD with some well-performed handcrafted shallow models. Extensive experiments on several benchmarks show that the proposed MSNSD outperforms the state-of-the-art saliency methods with less computational and memory complexity. Meanwhile, our aggregation method for saliency detection is effective and efficient to combine deep and shallow models and make them complementary to each other. Numéro de notice : A2020-601 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-019-01781-9 Date de publication en ligne : 09/12/2019 En ligne : https://doi.org/10.1007/s00371-019-01781-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95952
in The Visual Computer > vol 36 n° 9 (September 2020) . - pp 1883 - 1895[article]Ontologie d’Alerte Choucas : de la modélisation des connaissances à un outil support d’un raisonnement géovisuel / Matthieu Viry in Geomatica, vol 74 n° 3 (September 2020)
[article]
Titre : Ontologie d’Alerte Choucas : de la modélisation des connaissances à un outil support d’un raisonnement géovisuel Type de document : Article/Communication Auteurs : Matthieu Viry, Auteur ; Marlène Villanova-Oliver, Auteur Année de publication : 2020 Projets : CHOUCAS / Olteanu-Raimond, Ana-Maria Note générale : bibliographie Langues : Français (fre) Descripteur : [Termes IGN] interface graphique
[Termes IGN] ontologie
[Termes IGN] secours d'urgence
[Termes IGN] zone d'intérêt
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Lorsqu’une intervention de secours est nécessaire, localiser précisément et rapidement le site sur lequel envoyer les équipes est primordial. La littérature montre que des outils de géovisualisation constituent des solutions pertinentes pour supporter des processus d’analyse d’informations dans des contextes variés. Nous nous intéressons ici au raisonnement du secouriste réceptionnant un appel à l’aide et visons des solutions conceptuelles et logicielles dédiées à la tâche de détermination de la localisation de la victime, plus particulièrement dans le contexte du secours en montagne. Nous avons formalisé le raisonnement du secouriste et les informations sur lesquelles il ou elle s’appuie à l’aide d’une ontologie. L’Ontologie d’Alerte Choucas structure les concepts exploités par le secouriste qui élabore des hypothèses de localisation probable de la victime à partir d’informations (telles qu’une position relative, un temps de marche, une direction) fournies lors d’un échange verbal. Dans notre approche, l’ontologie est en outre exploitée pour dériver les composants d’interface d’un prototype de géovisualisation facilitant le raisonnement du secouriste. Ces composants sont une aide à la saisie des informations, en fournissant une restitution cartographique adaptée, et contribuent à construire et à affiner la zone de localisation. Notre approche présente une chaine de traitements originale, menant de la représentation des connaissances à la génération automatisée d’une interface fonctionnelle d’aide au raisonnement visant à localiser des victimes en montagne. Numéro de notice : A2020-840 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1139/geomat-2020-0005 En ligne : https://doi.org/10.1139/geomat-2020-0005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98319
in Geomatica > vol 74 n° 3 (September 2020)[article]Pansharpening: context-based generalized Laplacian pyramids by robust regression / Gemine Vivone in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)
[article]
Titre : Pansharpening: context-based generalized Laplacian pyramids by robust regression Type de document : Article/Communication Auteurs : Gemine Vivone, Auteur ; Stefano Marano, Auteur ; Jocelyn Chanussot, Auteur Année de publication : 2020 Article en page(s) : pp 6152 - 6167 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multirésolution
[Termes IGN] fonction de transfert de modulation
[Termes IGN] fusion d'images
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] lissage de données
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] régression
[Termes IGN] transformation en ondelettesRésumé : (auteur) Pansharpening refers to the combination of panchromatic (PAN) and multispectral (MS) images, designed to obtain a fused product retaining the fine spatial resolution of the former and the high spectral content of the latter. One of the most popular and successful approaches to pansharpening is the method known as context-based generalized Laplacian pyramid, which requires as a key ingredient for the estimation of the so-called injection coefficients. In this article, we propose the adoption of robust techniques for the estimation of the injection coefficients and detection strategies to select the clusters for which robust regression is needed, providing a suitable balancing between fusion performance and computational burden. Experimental results conducted on five real data sets acquired by the sensors QuickBird, WorldView-3, and WorldView-4, show the superiority of the proposed method with respect to current state-of-the-art pansharpening techniques. Numéro de notice : A2020-528 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2974806 Date de publication en ligne : 04/03/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2974806 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95706
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 9 (September 2020) . - pp 6152 - 6167[article]Post‐filtering with surface orientation constraints for stereo dense image matching / Xu Huang in Photogrammetric record, vol 35 n° 171 (September 2020)
[article]
Titre : Post‐filtering with surface orientation constraints for stereo dense image matching Type de document : Article/Communication Auteurs : Xu Huang, Auteur ; Rongjun Qin, Auteur Année de publication : 2020 Article en page(s) : pp 375-401 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] filtrage numérique d'image
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle stéréoscopique
[Termes IGN] orientation d'imageRésumé : (Auteur) Dense image matching (DIM) is a critical technique when computing accurate 3D geometric information for many photogrammetric applications. Most DIM methods adopt first‐order regularisation priors for efficient matching, which often introduce stepped biases (also called fronto‐parallel biases) into the matching results. To remove these biases and compute more accurate matching results, this paper proposes a novel post‐filtering method by adjusting the surface orientation of each pixel in the matching process. The core algorithm formulates the post‐filtering as the optimisation of a global energy function with second‐order regularisation priors. A compromise solution of the energy function is computed by breaking the optimisation into a collection of sub‐optimisations of each pixel in a local adaptive window. The proposed method was compared with several state‐of‐the‐art post‐filtering methods on indoor, aerial and satellite datasets. The comparisons demonstrate that the proposed method obtains the highest post‐filtering accuracies on all datasets. Numéro de notice : A2020-437 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12333 Date de publication en ligne : 20/09/2020 En ligne : https://doi.org/10.1111/phor.12333 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95843
in Photogrammetric record > vol 35 n° 171 (September 2020) . - pp 375-401[article]Precise extraction of citrus fruit trees from a Digital Surface Model using a unified strategy: detection, delineation, and clustering / Ali Ozgun Ok in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 9 (September 2020)PermalinkRecognition of building group patterns using graph convolutional network / Rong Zhao in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)PermalinkRelevé 3D et classification de nuages de points de patrimoine bâti / Arnadi Murtiyoso in XYZ, n° 164 (septembre 2020)PermalinkSemi-automatic building extraction from WorldView-2 imagery using taguchi optimization / Hasan Tonbul in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 9 (September 2020)PermalinkShip detection in SAR images via local contrast of Fisher vectors / Xueqian Wang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)PermalinkA spaceborne SAR-based procedure to support the detection of landslides / Giuseppe Esposito in Natural Hazards and Earth System Sciences, vol 20 n° 9 (September 2020)PermalinkThermal and spatial data integration for recreating rebuilding stages of wooden and masonry buildings / Paulina Lewińska in Photogrammetric record, vol 35 n° 171 (September 2020)PermalinkVehicle detection of multi-source remote sensing data using active fine-tuning network / Xin Wu in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)PermalinkX-ModalNet: A semi-supervised deep cross-modal network for classification of remote sensing data / Danfeng Hong in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)PermalinkShoreline extraction from WorldView2 satellite data in the presence of foam pixels using multispectral classification method / Audrey Minghelli in Remote sensing, vol 12 n° 16 (August-2 2020)PermalinkA regression model of spatial accuracy prediction for Openstreetmap buildings / Ibrahim Maidaneh Abdi in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2020 (August 2020)PermalinkSemCity Toulouse: a benchmark for building instance segmentation in satellite images / Ribana Roscher in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-5-2020 (August 2020)PermalinkAmbiguous use of geographical information systems for the rectification of large-scale geometric maps / Anders Wästfelt in Cartographic journal (the), Vol 57 n° 3 (August 2020)PermalinkBreaking the eyes: how do users get started with a coordinated and multiple view geovisualization tool? / Izabela Golebiowska in Cartographic journal (the), Vol 57 n° 3 (August 2020)PermalinkCan SPOT-6/7 CNN semantic segmentation improve Sentinel-2 based land cover products? sensor assessment and fusion / Olivier Stocker in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkCNN semantic segmentation to retrieve past land cover out of historical orthoimages and DSM: first experiments / Arnaud Le Bris in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkConjugate ruptures and seismotectonic implications of the 2019 Mindanao earthquake sequence inferred from Sentinel-1 InSAR data / Bingquan Li in International journal of applied Earth observation and geoinformation, vol 90 (August 2020)PermalinkCorrection of systematic radiometric inhomogeneity in scanned aerial campaigns using principal component analysis / Lâmân Lelégard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkDevelopment and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping / Alvin B. Baloloy in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)PermalinkExtraction of built-up areas from Landsat-8 OLI data based on spectral-textural information and feature selection using support vector machine method / Vijendra Singh Bramhe in Geocarto international, vol 35 n° 10 ([01/08/2020])PermalinkExtraction of urban built-up areas from nighttime lights using artificial neural network / Tingting Xu in Geocarto international, vol 35 n° 10 ([01/08/2020])PermalinkGeometric distortion of historical images for 3D visualization / Evelyn Paiz-Reyes in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkGuided feature matching for multi-epoch historical image blocks pose estimation / Lulin Zhang in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkIntegration of airborne gravimetry data filtering into residual least-squares collocation: example from the 1 cm geoid experiment / Martin Willberg in Journal of geodesy, vol 94 n° 8 (August 2020)PermalinkLeveraging photogrammetric mesh models for aerial-ground feature point matching toward integrated 3D reconstruction / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)PermalinkNear-real time forecasting and change detection for an open ecosystem with complex natural dynamics / Jasper A. Slingsby in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)PermalinkOn-Orbit Calibration of Terra MODIS VIS Bands Using Polarization-Corrected Desert Observations / Amit Angal in IEEE Transactions on geoscience and remote sensing, vol 58 n° 8 (August 2020)PermalinkPlanar polygons detection in lidar scans based on sensor topology enhanced Ransac / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkPredicting biomass dynamics at the national extent from digital aerial photogrammetry / Bronwyn Price in International journal of applied Earth observation and geoinformation, vol 90 (August 2020)PermalinkProvably consistent distributed Delaunay triangulation / Mathieu Brédif in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkRaytracing atmospheric delays in ground-based GNSS reflectometry / T. Nicolaidou in Journal of geodesy, vol 94 n° 8 (August 2020)PermalinkRecent changes in two outlet glaciers in the Antarctic Peninsula using multi-temporal Landsat and Sentinel-1 data / Carolina L. Simões in Geocarto international, vol 35 n° 11 ([01/08/2020])PermalinkStructure from motion for complex image sets / Mario Michelini in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)PermalinkTowards structureless bundle adjustment with two- and three-view structure approximation / Ewelina Rupnik in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkA worldwide 3D GCP database inherited from 20 years of massive multi-satellite observations / Laure Chandelier in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkAn improved constrained simultaneous iterative reconstruction technique for ionospheric tomography / Yi Bin Yao in GPS solutions, Vol 24 n° 3 (July 2020)PermalinkAssessment of USGS DEMs for modelling pothole inundation in the prairie pothole region of Iowa / Priyadarshi Upadhyay in Geocarto international, vol 35 n° 9 ([01/07/2020])PermalinkClassification of hyperspectral and LiDAR data using coupled CNNs / Renlong Hang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkClassification of sea ice types in Sentinel-1 SAR data using convolutional neural networks / Hugo Boulze in Remote sensing, vol 12 n° 13 (July-1 2020)PermalinkComplete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China / Kun Tan in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)PermalinkComputational improvements to multi-scale geographically weighted regression / Ziqi Li in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)PermalinkDense stereo matching strategy for oblique images that considers the plane directions in urban areas / Jianchen Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkEffect of spatial correlation on the performances of modernized GPS and Galileo in relative positioning / Noureddine Kheloufi in Geodesy and cartography, vol 46 n° 2 (July 2020)PermalinkEvaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches / S.M. Hamylton in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)PermalinkImproved depth estimation for occlusion scenes using a light-field camera / Changkun Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 7 (July 2020)PermalinkA novel framework based on polarimetric change vectors for unsupervised multiclass change detection in dual-pol intensity SAR images / David Pirrone in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkRethinking error estimations in geospatial data: the correct way to determine product accuracy / Qassim Abdullah in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 7 (July 2020)PermalinkRoles of horizontal and vertical tree canopy structure in mitigating daytime and nighttime urban heat island effects / Jike Chen in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)PermalinkSemi-automatic identification of submarine pipelines with synthetic aperture sonar Images / Victor Hugo Fernandes in Marine geodesy, Vol 43 n° 4 (July 2020)PermalinkA simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques / Olutoyin Adeola Fashae in Geocarto international, vol 35 n° 9 ([01/07/2020])PermalinkSimulating urban land use change by integrating a convolutional neural network with vector-based cellular automata / Yaqian Zhai in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)PermalinkSubpixel-pixel-superpixel-based multiview active learning for hyperspectral images classification / Yu Li in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkAccuracy assessment of real-time kinematics (RTK) measurements on unmanned aerial vehicles (UAV) for direct geo-referencing / Desta Ekaso in Geo-spatial Information Science, vol 23 n° 2 (June 2020)PermalinkALERT: adversarial learning with expert regularization using Tikhonov operator for missing band reconstruction / Litu Rout in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkAn Illumination Insensitive descriptor combining the CSLBP features for street view images in augmented reality: experimental studies / Zejun Xiang in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkAn integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis / Lei Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkAqueous alteration mapping in Rishabdev ultramafic complex using imaging spectroscopy / Hrishikesh Kumar in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)PermalinkCounting of grapevine berries in images via semantic segmentation using convolutional neural networks / Laura Zabawa in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkDigital terrain, surface, and canopy height models from InSAR backscatter-height histograms / Gustavo H.X. Shiroma in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkEnsemble learning for hyperspectral image classification using tangent collaborative representation / Hongjun Su in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkEstimating and interpreting fine-scale gridded population using random forest regression and multisource data / Yun Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkFine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data / Shivangi Srivastava in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)PermalinkGeometric modelling and calibration of a spherical camera imaging system / Derek D. Lichti in Photogrammetric record, vol 35 n° 170 (June 2020)PermalinkGeoNat v1.0: A dataset for natural feature mapping with artificial intelligence and supervised learning / Samantha T. Arundel in Transactions in GIS, Vol 24 n° 3 (June 2020)PermalinkA hybrid deep learning–based model for automatic car extraction from high-resolution airborne imagery / Mehdi Khoshboresh Masouleh in Applied geomatics, vol 12 n° 2 (June 2020)PermalinkHyperspectral classification with noisy label detection via superpixel-to-pixel weighting distance / Bing Tu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkImproved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkIndoor positioning using PnP problem on mobile phone images / Hana Kubickova in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkModélisation d'une maquette sur la base de données LiDAR et intégration d'un projet 3D / Julien Brunner in Géomatique suisse, vol 118 n° 6 (juin 2020)PermalinkMountain summit detection with Deep Learning: evaluation and comparison with heuristic methods / Rocio Nahime Torres in Applied geomatics, vol 12 n° 2 (June 2020)PermalinkObject-based automatic multi-index built-up areas extraction method for WorldView-2 satellite imagery / Zhenhui Sun in Geocarto international, Vol 35 n° 8 ([01/06/2020])PermalinkPhotogrammetric determination of 3D crack opening vectors from 3D displacement fields / Frank Liebold in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkPolarimetric SAR calibration and residual error estimation when corner reflectors are unavailable / Lei Shi in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkPotential of texture from SAR tomographic images for forest aboveground biomass estimation / Zhanmang Liao in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)PermalinkSubpixel SAR image registration through parabolic interpolation of the 2-D cross correlation / Luca Pallotta in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkTraffic signal detection from in-vehicle GPS speed profiles using functional data analysis and machine learning / Yann Méneroux in International Journal of Data Science and Analytics JDSA, vol 10 n° 1 (June 2020)PermalinkTrajectory drift–compensated solution of a stereo RGB-D mapping system / Shengjun Tang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 6 (June 2020)PermalinkUnsupervised change detection between SAR images based on hypergraphs / Jun Wang in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkAbove-ground biomass estimation of arable crops using UAV-based SfM photogrammetry / Maria Luz Gil-Docampo in Geocarto international, vol 35 n° 7 ([15/05/2020])PermalinkA water identification method basing on grayscale Landsat 8 OLI images / Zhitian Deng in Geocarto international, vol 35 n° 7 ([15/05/2020])PermalinkAn integrated approach to registration and fusion of hyperspectral and multispectral images / Yuan Zhou in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkAssessing alternative methods for unsupervised segmentation of urban vegetation in very high-resolution multispectral aerial imagery / Allison Lassiter in Plos one, vol 15 n° 5 (May 2020)PermalinkAssessment of the accuracy of DTM river bed model using classical surveying measurement and LiDAR: a case study in Poland / Pawel Kotlarz in Survey review, vol 52 n° 372 (May 2020)PermalinkAutomated conflation of digital elevation model with reference hydrographic lines / Timofey Samsonov in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)PermalinkAutomatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks / Mahmoud Saeedimoghaddam in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)PermalinkComparing the roles of landmark visual salience and semantic salience in visual guidance during indoor wayfinding / Weihua Dong in Cartography and Geographic Information Science, vol 47 n° 3 (May 2020)PermalinkA convolutional neural network with mapping layers for hyperspectral image classification / Rui Li in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkDeep learning for enrichment of vector spatial databases: Application to highway interchange / Guillaume Touya in ACM Transactions on spatial algorithms and systems, TOSAS, vol 6 n° 3 (May 2020)PermalinkDiscrimination of different sea ice types from CryoSat-2 satellite data using an Object-based Random Forest (ORF) / Su Shu in Marine geodesy, Vol 43 n° 3 (May 2020)PermalinkFootprint determination of a spectroradiometer mounted on an unmanned aircraft system / Deepak Gautam in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkFusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)PermalinkGeomorphic Change Detection Using Cost-Effective Structure-from-Motion Photogrammetry: Evaluation of Direct Georeferencing from Consumer-Grade UAS at Orewa Beach (New Zealand) / Stéphane Bertin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 5 (May 2020)PermalinkIntertidal topography mapping using the waterline method from Sentinel-1 & -2 images: The examples of Arcachon and Veys Bays in France / Edward Salameh in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkMapping urban grey and green structures for liveable cities using a 3D enhanced OBIA approach and vital statistics / E. Banzhaf in Geocarto international, vol 35 n° 6 ([01/05/2020])PermalinkModeling strawberry biomass and leaf area using object-based analysis of high-resolution images / Zhen Guan in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)Permalink