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Titre : Advanced sensors for real-time monitoring applications Type de document : Monographie Auteurs : Olga Korostynska, Éditeur scientifique ; Alex Mason, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 350 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-3-0365-0427-8 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] capteur actif
[Termes IGN] capteur imageur
[Termes IGN] capteur ultrasonore
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] surveillance
[Termes IGN] temps réelRésumé : (éditeur) It is impossible to imagine the modern world without sensors, or without real-time information about almost everything—from local temperature to material composition and health parameters. We sense, measure, and process data and act accordingly all the time. In fact, real-time monitoring and information is key to a successful business, an assistant in life-saving decisions that healthcare professionals make, and a tool in research that could revolutionize the future. To ensure that sensors address the rapidly developing needs of various areas of our lives and activities, scientists, researchers, manufacturers, and end-users have established an efficient dialogue so that the newest technological achievements in all aspects of real-time sensing can be implemented for the benefit of the wider community. This book documents some of the results of such a dialogue and reports on advances in sensors and sensor systems for existing and emerging real-time monitoring applications. Note de contenu : 1- Real-time water quality monitoring with chemical sensors
2- Body condition score estimation based on regression analysis using a 3D camera
3- Wireless module for nondestructive testing/structural health monitoring applications based on solitary waves
4- Quantified activity measurement for medical use in movement disorders through IR-UWB radar sensor
5- Pre-pressure optimization for ultrasonic motors based on multi-sensor fusion
6- On-line monitoring of pipe wall thinning by a high temperature ultrasonic waveguide system at the flow accelerated corrosion proof facility
7- A low-cost continuous turbidity monitor
8- Laboratory calibration and field validation of soil water content and salinity measurements using the 5TE sensor
9- Quantitative analysis of elements in fertilizer using laser-induced breakdown spectroscopy coupled with support vector regression model
10- Univariate and multivariate analysis of phosphorus element in fertilizers using laser-induced breakdown spectroscopy
11- The efficiency of color space channels to quantify color and color intensity change in liquids, pH strips, and lateral flow assays with smartphones
12- An innovative ultrasonic apparatus and technology for diagnosis of freeze-drying process
13- Temperature and strain correlation of bridge parallel structure based on vibrating wire strain sensor
14- Train hunting related fast degradation of a railway crossing—condition monitoring and numerical verification
15- Correlation analysis and verification of railway crossing condition monitoring
16- A novel monitoring approach for train tracking and incursion detection in underground structures based on ultra-weak FBG sensing array
17- Digital approach to rotational speed measurement using an electrostatic sensor
18- Multi-factor operating condition recognition using 1D convolutional long short-term network
19- Comprehensive improvement of the sensitivity and detectability of a large-aperture electromagnetic wear particle detector
20- Analysis of satellite compass error’s spectrumNuméro de notice : 28598 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-0427-8 En ligne : https://doi.org/10.3390/books978-3-0365-0427-8 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99377 Introducing diversion graph for real-time spatial data analysis with location based social networks / Sameera Kannangara (2021)
Titre : Introducing diversion graph for real-time spatial data analysis with location based social networks Type de document : Article/Communication Auteurs : Sameera Kannangara, Auteur ; Hairuo Xie, Auteur ; Egemen Tanin, Auteur ; Aaron Harwood, Auteur ; Shanika Karunasekera, Auteur Editeur : Leibniz [Allemagne] : Schloss Dagstuhl – Leibniz-Zentrum für Informatik Année de publication : 2021 Conférence : GIScience 2021, 11th International Conference on Geographic Information Science 27/09/2021 30/09/2021 Poznań Pologne Open Access Proceedings Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] chemin le plus court, algorithme du
[Termes IGN] graphe
[Termes IGN] image Flickr
[Termes IGN] objet mobile
[Termes IGN] réseau social géodépendant
[Termes IGN] temps réel
[Termes IGN] triangulation de Delaunay
[Termes IGN] TwitterRésumé : (auteur) Neighbourhood graphs are useful for inferring the travel network between locations posted in the Location Based Social Networks (LBSNs). Existing neighbourhood graphs, such as the Stepping Stone Graph lack the ability to process a high volume of LBSN data in real time. We propose a neighbourhood graph named Diversion Graph, which uses an efficient edge filtering method from the Delaunay triangulation mechanism for fast processing of LBSN data. This mechanism enables Diversion Graph to achieve a similar accuracy level as Stepping Stone Graph for inferring travel networks, but with a reduction of the execution time of over 90%. Using LBSN data collected from Twitter and Flickr, we show that Diversion Graph is suitable for travel network processing in real time. Numéro de notice : C2021-079 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Communication DOI : 10.4230/LIPIcs.GIScience.2021.I.7 Date de publication en ligne : 25/09/2020 En ligne : https://doi.org/10.4230/LIPIcs.GIScience.2021.I.7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100930 Real-time multimodal semantic scene understanding for autonomous UGV navigation / Yifei Zhang (2021)
Titre : Real-time multimodal semantic scene understanding for autonomous UGV navigation Type de document : Thèse/HDR Auteurs : Yifei Zhang, Auteur ; Fabrice Mériaudeau, Directeur de thèse ; Désiré Sidibé, Directeur de thèse Editeur : Dijon : Université Bourgogne Franche-Comté UBFC Année de publication : 2021 Importance : 114 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse pour obtenir le doctorat de l'Université Bourgogne Franche-Comté, Spécialité Instrumentation et informatique d’imageLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] données polarimétriques
[Termes IGN] fusion d'images
[Termes IGN] image RVB
[Termes IGN] intégration de données
[Termes IGN] navigation autonome
[Termes IGN] segmentation sémantique
[Termes IGN] temps réel
[Termes IGN] véhicule sans piloteIndex. décimale : THESE Thèses et HDR Résumé : (Auteur) Robust semantic scene understanding is challenging due to complex object types, as well as environmental changes caused by varying illumination and weather conditions. This thesis studies the problem of deep semantic segmentation with multimodal image inputs. Multimodal images captured from various sensory modalities provide complementary information for complete scene understanding. We provided effective solutions for fully-supervised multimodal image segmentation and few-shot semantic segmentation of the outdoor road scene. Regarding the former case, we proposed a multi-level fusion network to integrate RGB and polarimetric images. A central fusion framework was also introduced to adaptively learn the joint representations of modality-specific features and reduce model uncertainty via statistical post-processing.In the case of semi-supervised semantic scene understanding, we first proposed a novel few-shot segmentation method based on the prototypical network, which employs multiscale feature enhancement and the attention mechanism. Then we extended the RGB-centric algorithms to take advantage of supplementary depth cues. Comprehensive empirical evaluations on different benchmark datasets demonstrate that all the proposed algorithms achieve superior performance in terms of accuracy as well as demonstrating the effectiveness of complementary modalities for outdoor scene understanding for autonomous navigation. Note de contenu : 1. Introduction
1.1 Context and Motivation
1.2 Background and Challenges
1.3 Contributions
1.4 Organization
2. Background on Neural Networks
2.1 Basic Concepts
2.2 Neural Network Layers
2.3 Optimization
2.4 Model Training
2.5 Evaluation Metrics
2.6 Summary
3. Literature Review
3.1 Fully-supervised Semantic Image
3.2 Datasets
3.3 Summary
4. Deep Multimodal Fusion for Semantic Image Segmentation
4.1 CMNet: Deep Multimodal Fusion
4.2 A Central Multimodal Fusion Framework
4.3 Summary
5. Few-shot Semantic Image Segmentation
5.1 Introduction on Few-shot Segmentation
5.2 MAPnet: A Multiscale Attention-Based Prototypical Network
5.3 RDNet: Incorporating Depth Information into Few-shot Segmentation
5.4 Summary
6. Conclusion and Future Work
6.1 General Conclusion
6.2 Future PerspectivesNuméro de notice : 26527 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Instrumentation et informatique d’image : Bourgogne : 2021 nature-HAL : Thèse Date de publication en ligne : 02/03/2021 En ligne : https://hal.science/tel-03154783v1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97556 SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery / Marie Ballère in Remote sensing of environment, Vol 252 (January 2021)
[article]
Titre : SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery Type de document : Article/Communication Auteurs : Marie Ballère , Auteur ; Alexandre Bouvet, Auteur ; Stéphane Mermoz, Auteur ; Thuy Le Toan, Auteur ; Thierry Koleck, Auteur ; Caroline Bedeau, Auteur ; Mathilde André, Auteur ; Elodie Forestier, Auteur ; Pierre-Louis Frison , Auteur ; Cédric Lardeux, Auteur Année de publication : 2021 Projets : 1-Pas de projet / Article en page(s) : n° 112159 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] forêt tropicale
[Termes IGN] Guyane (département français)
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] surveillance forestière
[Termes IGN] temps réelRésumé : (auteur) French Guiana forests cover 8 million hectares. With 98% of emerged land covered by forests, French Guiana is the area with the highest proportion of forest cover in the world. These forests are home to an exceptionally rich and diverse wealth of biodiversity that is both vulnerable and under threat due to high levels of pressure from human activity. As part of the French territory, French Guiana benefits from determined and continuous national efforts in the preservation of biodiversity and the environmental functionalities of ecosystems. The loss and fragmentation of forest cover caused by gold mining (legal and illegal), smallholder agriculture and forest exploitation, are considered as small-scale disturbances, although representing strong effects to vulnerable natural habitats, landscapes, and local populations. To monitor forest management programs and combat illegal deforestation and forest opening near-real time alerts system based on remote sensing data are required. For this large territory under frequent cloud cover, Synthetic-Aperture Radar (SAR) data appear to be the best adapted. In this paper, a method for forest alerts in a near-real time context based on Sentinel-1 data over the whole of French Guiana (83,534 km2) was developed and evaluated. The assessment was conducted for 2 years between 2016 and 2018 and includes comparisons with reference data provided by French Guiana forest organizations and comparisons with the existing University of Maryland Global Land Analysis and Discovery Forest Alerts datasets based on Landsat data. The reference datasets include 1,867 plots covering 2,124.5 ha of gold mining, smallholder agriculture and forest exploitation. The validation results showed high user accuracies (96.2%) and producer accuracies (81.5%) for forest loss detection, with the latter much higher than for optical forest alerts (36.4%). The forest alerts maps were also compared in terms of detection timing, showing systematic temporal delays of up to one year in the optical method compared to the SAR method. These results highlight the benefits of SAR over optical imagery for forest alerts detection in French Guiana. Finally, the potential of the SAR method applied to tropical forests is discussed. The SAR-based map of this study is available on http://cesbiomass.net/. Numéro de notice : A2021-066 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2020.112159 Date de publication en ligne : 05/11/2020 En ligne : https://doi.org/10.1016/j.rse.2020.112159 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96937
in Remote sensing of environment > Vol 252 (January 2021) . - n° 112159[article]Evolution of orbit and clock quality for real-time multi-GNSS solutions / Kamil Kazmierski in GPS solutions, Vol 24 n° 4 (October 2020)
[article]
Titre : Evolution of orbit and clock quality for real-time multi-GNSS solutions Type de document : Article/Communication Auteurs : Kamil Kazmierski, Auteur ; Radoslaw Zajdel, Auteur ; Krzysztof Sosnica, Auteur Année de publication : 2020 Article en page(s) : 12 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] correction
[Termes IGN] erreur systématique
[Termes IGN] horloge atomique
[Termes IGN] orbitographie par GNSS
[Termes IGN] positionnement par GNSS
[Termes IGN] positionnement ponctuel précis
[Termes IGN] précision du positionnement
[Termes IGN] synchronisation
[Termes IGN] télémétrie laser sur satellite
[Termes IGN] temps réelRésumé : (auteur) High-quality satellite orbits and clocks are necessary for multi-GNSS precise point positioning and timing. In undifferenced GNSS solutions, the quality of orbit and clock products significantly influences the resulting position accuracy; therefore, for precise positioning in real time, the corrections for orbits and clocks are generated and distributed to users. In this research, we assess the quality and the availability of real-time CNES orbits and clocks for GPS, GLONASS, Galileo, and BeiDou-2 separated by satellite blocks and types, as well as the product quality changes over time. We calculate the signal-in-space ranging error (SISRE) as the main orbit and clock quality indicator. Moreover, we employ independent orbit validation based on satellite laser ranging. We found that the most accurate orbits are currently available for GPS. However, Galileo utmost stable atomic clocks compensate for systematic errors in Galileo orbits. As a result, the SISRE for Galileo is lower than that for GPS, equaling 1.6 and 2.3 cm for Galileo and GPS, respectively. The GLONASS satellites, despite the high quality of their orbits, are characterized by poor quality of clocks, and together with BeiDou-2 in medium and geosynchronous inclined orbits, are characterized by SISRE of 4–6 cm. BeiDou-2 in geostationary orbits is characterized by large orbital errors and the lowest availability of real-time orbit and clock corrections due to a large number of satellite maneuvers. The quality of GNSS orbit and clock corrections changes over time and depends on satellite type, block, orbit characteristics, onboard atomic clock, and the sun elevation above the orbital plane. Numéro de notice : A2020-520 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-01026-6 Date de publication en ligne : 28/08/2020 En ligne : https://doi.org/10.1007/s10291-020-01026-6 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95687
in GPS solutions > Vol 24 n° 4 (October 2020) . - 12 p.[article]An offshore real-time precise point positioning technique based on a single set of BeiDou short-message communication devices / Zhixi Nie in Journal of geodesy, vol 94 n° 9 (September 2020)PermalinkGipsyX/RTGx, a new tool set for space geodetic operations and research / Willy I. Bertiger in Advances in space research, vol 66 n° 3 (1 August 2020)PermalinkCyclists' exposure to air pollution and noise in Mexico City : contribution of real-time traffic density indicators integrated into GIS / Philippe Apparicio in Revue internationale de géomatique, vol 30 n° 3-4 (juillet - décembre 2020)PermalinkPerformance of real-time undifferenced precise positioning assisted by remote IGS multi-GNSS stations / Zhiqiang Liu in GPS solutions, vol 24 n° 2 (April 2020)PermalinkAssessing public transit performance using real-time data: spatiotemporal patterns of bus operation delays in Columbus, Ohio, USA / Yongha Park in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)PermalinkReal-time mapping of natural disasters using citizen update streams / Iranga Subasinghe in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)PermalinkPermalinkEstimation and representation of regional atmospheric corrections for augmenting real-time single-frequency PPP / Peiyuan Zhou in GPS solutions, vol 24 n° 1 (January 2020)PermalinkPermalinkPermalinkPermalinkSpatio-Temporal Prediction of the Epidemic Spread of Dangerous Pathogens Using Machine Learning Methods / Wolfgang B. Hamer in ISPRS International journal of geo-information, Vol 9 n° 1 (January 2020)PermalinkSystème de traitement d’images temps réel dédié à la mesure de champs denses de déplacements et de déformations / Seyfeddine Boukhtache (2020)PermalinkPermalinkApport de données atmosphériques sur le temps de convergence du PPP centimétrique temps réel / Iris de Gelis in XYZ, n° 161 (décembre 2019)PermalinkKalman-filter-based undifferenced cycle slip estimation in real-time precise point positioning / Pan Li in GPS solutions, vol 23 n° 4 (October 2019)PermalinkPerformance evaluation of real-time global ionospheric maps provided by different IGS analysis centers / Xiaodong Ren in GPS solutions, vol 23 n° 4 (October 2019)PermalinkPerformance of Galileo-only dual-frequency absolute positioning using the fully serviceable Galileo constellation / Tomasz Hadas in GPS solutions, vol 23 n° 4 (October 2019)PermalinkReal-time clock prediction of multi-GNSS satellites and its application in precise point positioning / Yaquan Peng in Advances in space research, vol 64 n°7 (1 October 2019)PermalinkEvaluating the impact of higher-order ionospheric corrections on multi-GNSS ultra-rapid orbit determination / Xinghan Chen in Journal of geodesy, vol 93 n° 9 (September 2019)Permalink