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Hyperspectral 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)
[article]
Titre : Hyperspectral classification with noisy label detection via superpixel-to-pixel weighting distance Type de document : Article/Communication Auteurs : Bing Tu, Auteur ; Chengle Zhou, Auteur ; Danbing He, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 4116 - 4131 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données étiquetées d'entrainement
[Termes IGN] erreur d'échantillon
[Termes IGN] image hyperspectrale
[Termes IGN] pondération
[Termes IGN] précision de la classification
[Termes IGN] superpixelRésumé : (auteur) Classification is an important technique for remotely sensed hyperspectral image (HSI) exploitation. Often, the presence of wrong (noisy) labels presents a drawback for accurate supervised classification. In this article, we introduce a new framework for noisy label detection that combines a superpixel-to-pixel weighting distance (SPWD) and density peak clustering. The proposed method is able to accurately detect and remove noisy labels in the training set before HSI classification. It considers two weak assumptions when exploiting the spectral–spatial information contained in the HSI: 1) all the pixels in a superpixel belong to the same class and 2) close pixels in spectral space have the same label. The proposed method consists of the following steps. First, a superpixel segmentation step is used to obtain self-adaptive spatial information for each training sample. Then, a metric is utilized to measure the spectral distance information between each superpixel and pixel. Meanwhile, in order to overcome the first weak assumption, we use K nearest neighbors to obtain the closest neighborhoods of pixels around each superpixel, and a Gaussian weight is employed to mitigate the second weak assumption by adapting the original distance information. Next, the noisy labels in the original training set are removed by a density threshold-based decision function. Finally, the support vector machine (SVM) classifier is employed to evaluate the effectiveness of the proposed SPWD detection method in terms of classification accuracy. Experiments performed on several real HSI data sets demonstrate that the method can effectively improve the performance of classifiers trained with noisy training sets in terms of classification accuracy. Numéro de notice : A2020-283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2961141 Date de publication en ligne : 13/01/2020 En ligne : https://doi.org/10.1109/TGRS.2019.2961141 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95105
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 6 (June 2020) . - pp 4116 - 4131[article]Using GIS for disease mapping and clustering in Jeddah, Saudi Arabia / Abdulkader Murad in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)
[article]
Titre : Using GIS for disease mapping and clustering in Jeddah, Saudi Arabia Type de document : Article/Communication Auteurs : Abdulkader Murad, Auteur ; Bandar Fuad Khashoggi, Auteur Année de publication : 2020 Article en page(s) : 22 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse de groupement
[Termes IGN] Arabie Saoudite
[Termes IGN] carte sanitaire
[Termes IGN] distribution spatiale
[Termes IGN] estimation par noyau
[Termes IGN] modélisation environnementale
[Termes IGN] modélisation spatiale
[Termes IGN] surveillance sanitaire
[Termes IGN] zone à risqueRésumé : (auteur) Geographic information systems (GIS) can be used to map the geographical distribution of the prevalence of disease, trends in disease transmission, and to spatially model environmental aspects of disease occurrence. The aim of this study is to discuss a GIS application created to produce mapping and cluster modeling of three diseases in Jeddah, Saudi Arabia: diabetes, asthma, and hypertension. Data about these diseases were obtained from health centers’ registered patient records. These data were spatially evaluated using several spatial–statistical analytical models, including kernel and hotspot models. These models were created to explore and display the disparate patterns of the selected diseases and to illustrate areas of high concentration, and may be invaluable in understanding local patterns of diseases and their geographical associations. Numéro de notice : A2020-300 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050328 Date de publication en ligne : 18/05/2020 En ligne : https://doi.org/10.3390/ijgi9050328 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95140
in ISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - 22 p.[article]A framework for extracting urban functional regions based on multiprototype word embeddings using points-of-interest data / Sheng Hu in Computers, Environment and Urban Systems, vol 80 (March 2020)
[article]
Titre : A framework for extracting urban functional regions based on multiprototype word embeddings using points-of-interest data Type de document : Article/Communication Auteurs : Sheng Hu, Auteur ; Zhanjun He, Auteur ; Liang Wu, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] données massives
[Termes IGN] espace urbain
[Termes IGN] extraction de données
[Termes IGN] gestion urbaine
[Termes IGN] image à haute résolution
[Termes IGN] point d'intérêt
[Termes IGN] regroupement de données
[Termes IGN] télédétection spatiale
[Termes IGN] traitement du langage naturel
[Termes IGN] Wuhan (Chine)
[Termes IGN] zone urbaineRésumé : (auteur) Many studies are in an effort to explore urban spatial structure, and urban functional regions have become the subject of increasing attention among planners, engineers and public officials. Attempts have been made to identify urban functional regions using high spatial resolution (HSR) remote sensing images and extensive geo-data. However, the research scale and throughput have also been limited by the accessibility of HSR remote sensing data. Recently, big geo-data are becoming increasingly popular for urban studies since research is still accessible and objective with regard to the use of these data. This study aims to build a novel framework to provide an alternative solution for sensing urban spatial structure and discovering urban functional regions based on emerging geo-data – points of interest (POIs) data and an embedding learning method in the natural language processing (NLP) field. We started by constructing the intraurban functional corpus using a center-context pairs-based approach. A word embeddings representation model for training that corpus was used to extract multiprototype vectors in the second step, and the last step aggregated the functional parcels based on an introduced spatial clustering method, hierarchical density-based spatial clustering of applications with noise (HDBSCAN). The clustering results suggested that our proposed framework used in this study is capable of discovering the utilization of urban space with a reasonable level of accuracy. The limitation and potential improvement of the proposed framework are also discussed. Numéro de notice : A2020-191 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2019.101442 Date de publication en ligne : 15/11/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101442 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94853
in Computers, Environment and Urban Systems > vol 80 (March 2020)[article]Analyse de la distribution spatiale des implantations humaines : apports et limites d’indicateurs multi-échelles et trans-échelles / François Sémécurbe (2020)
Titre : Analyse de la distribution spatiale des implantations humaines : apports et limites d’indicateurs multi-échelles et trans-échelles Type de document : Thèse/HDR Auteurs : François Sémécurbe, Auteur ; Cécile Tannier, Directeur de thèse ; Stéphane Roux, Directeur de thèse Editeur : Dijon : Université Bourgogne Franche-Comté UBFC Année de publication : 2020 Importance : 231 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de Doctorat de l'établissement Université Bourgogne Franche- Comté, spécialité GéographieLangues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] analyse en composantes principales
[Termes IGN] analyse fractale
[Termes IGN] apprentissage profond
[Termes IGN] distribution spatiale
[Termes IGN] étalement urbain
[Termes IGN] fonction K de Ripley
[Termes IGN] France (administrative)
[Termes IGN] géographie humaine
[Termes IGN] invariance
[Termes IGN] population
[Termes IGN] répartition géographique
[Termes IGN] représentation multiple
[Termes IGN] transformation en ondelettesIndex. décimale : THESE Thèses et HDR Résumé : (auteur) En tant qu'être humain, il nous est aisé de juger visuellement du caractère dispersé ou concentré d'une distribution. Pour autant, la formalisation quantitative de nos impressions est problématique. Elle est tributaire des échelles d'analyse choisies. Cette dépendance des indicateurs aux échelles a changé de statut. Initialement considérée comme un frein à la connaissance, elle témoigne à présent de l'organisation multi-échelle des distributions étudiées. L'objectif central de cette thèse est d'approfondir les limites et l'apport des indicateurs multi-échelles et trans-échelles à l'étude des distributions spatiales des implantations humaines. L'analyse spatiale vise à comparer les distributions spatiales à une répartition uniforme. La manière dont on s'éloigne de cette référence est utilisée pour caractériser l'organisation multi-échelle des distributions analysées. L'application de ces méthodes aux implantations humaines n'a pas été satisfaisante. Le recours à une référence exogène n'est pas adapté à des distributions très inégalement concentrées dans l'espace. L'analyse fractale, fréquemment utilisée en géographie urbaine, considère que les distributions analysées sont leur propre étalon de mesure. Les dimensions fractales mesurent la façon dont l'espace occupé par celles-ci évolue à travers les échelles. Ce type d'analyse requiert une régularité entre les échelles, l'invariance d'échelle dont l'existence n'est pas vérifiée sur l'ensemble des territoires. L'analyse trans-échelle généralise les principes de l'analyse fractale à toutes les distributions et permet de caractériser l'inégale concentration des implantations humaines dans les territoires ruraux et urbains. Note de contenu : 1- Introduction
2- Méthodes de statistique spatiale pour l’analyse de la distribution spatiale des bâtiments
3- Méthodes d’analyses fractales et multifractales pour l’analyse de la distribution spatiale des bâtiments, de la population et des formes d’occupation du sol
4- Dépasser le présupposé d’invariance d’échelle via l’analyse des signatures trans-échelles
5- ConclusionNuméro de notice : 28444 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Géographie : Bourgogne : 2020 Organisme de stage : Laboratoire THEMA Théoriser et modéliser pour aménager DOI : sans En ligne : https://tel.hal.science/tel-03125388/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98894 Application of digital image processing in automated analysis of insect leaf mines / Yee Man Theodora Cho (2020)
Titre : Application of digital image processing in automated analysis of insect leaf mines Type de document : Thèse/HDR Auteurs : Yee Man Theodora Cho, Auteur Editeur : York [Royaume-Uni] : University of York Année de publication : 2020 Importance : 202 p. Format : 21 x 30 cm Note générale : bibliographie
PhD thesis, Electronic Engineering, University of York, United KingdomLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Acer (genre)
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage automatique
[Termes IGN] Castanea (genre)
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] détection de contours
[Termes IGN] diagnostic foliaire
[Termes IGN] image hyperspectrale
[Termes IGN] insecte nuisible
[Termes IGN] modèle de simulation
[Termes IGN] segmentation d'image
[Termes IGN] seuillage
[Termes IGN] surveillance de la végétation
[Termes IGN] taxinomie
[Termes IGN] traitement d'imageRésumé : (auteur) Automated species identificationhas become a popular alternative to manual classification in the past few decades, as a result of advancement in digital image processing techniques and machine learning algorithms. This project aims to devise a new approach for the detection of leaf mines and fungal spots from digital images, and to investigate the possibility of monitoring the growth of leaf mines. Leaf-mining insects primarily belong to the orders of moths (Lepidoptera), flies (Diptera) and beetles (Coleoptera); or the suborders of sawflies (Symphyta) and wasps (Apocrita). Every spring and summer the larvae of leaf-mining insects feed on leaf tissues until maturity and vacate the mines as adults. As most species of leaf miners attack garden plants or crops, they are generally regarded as pests, despiterarely causing severe long-term detrimental effect on their host plants. Increase in human activities has led to the spread of these invasive species globally in recent years, and the demand for an effective classification system to monitor their distribution is rising consistently. Samples from three species of leaf-mining insects were included in this project: horse chestnut leaf miner (Cameraria ohridella), apple leaf miner (Lyonetia clerkella), and holly leaf miner (Phytomyza ilicis). Leaves with tar spots (Rhytisma acerinum)were also introduced as variations.The proposed method uses image processing techniques such as thresholding, conversion between colour spaces, edge detection, image segmentation,and morphological operations. This project also explores the use of machine learning algorithmsas analytical monitoring and predictive tools, using the growth of C. ohridellaleaf mines as an example. Note de contenu : 1- Introduction
2- Background
3- Digital image processing
4- Automated classification
5- Implementation
6- Data analysis
7- ConclusionNuméro de notice : 28552 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : PhD thesis : Electronic Engineering : University of York : 2020 En ligne : https://etheses.whiterose.ac.uk/27749/1/Cho_105036528_Thesis.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97414 PermalinkPotential of UAV photogrammetry for characterization of forest canopy structure in uneven-aged mixed conifer–broadleaf forests / Sadeepa Jayathunga in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)PermalinkUnsupervised classification of multispectral images embedded with a segmentation of panchromatic images using localized clusters / Ting Mao in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)PermalinkA reliable traffic prediction approach for bike‐sharing system by exploiting rich information with temporal link prediction strategy / Yan Zhou in Transactions in GIS, Vol 23 n° 5 (October 2019)PermalinkSpatially constrained regionalization with multilayer perceptron / Michael Govorov in Transactions in GIS, Vol 23 n° 5 (October 2019)PermalinkGenetic diversity and structure of Silver fir (Abies alba Mill.) at the south-eastern limit of its distribution range / Maria Teodosiu in Annals of forest research, vol 62 n° 2 (June - December 2019)PermalinkPiecewise-planar approximation of large 3D data as graph-structured optimization / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2/W5 (May 2019)PermalinkExploring the uncertainty of activity zone detection using digital footprints with multi-scaled DBSCAN / Xinyi Liu in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)PermalinkA natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements / Yingjie Hu in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)PermalinkUsing LiDAR to develop high-resolution reference models of forest structure and spatial pattern / Haley L. 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Sjahputera in IEEE Transactions on geoscience and remote sensing, vol 49 n° 12 Tome 1 (December 2011)PermalinkComputational method for the point cluster analysis on networks / K. Sugihara in Geoinformatica, vol 15 n° 1 (January 2011)PermalinkA framework for regional association rule mining and scoping in spatial datasets / W. Ding in Geoinformatica, vol 15 n° 1 (January 2011)PermalinkL’impact du voisinage géographique des pays dans l’attribution des votes au Concours Eurovision de la Chanson / Jean-François Gleyze in Cybergeo, European journal of geography, n° 2011 ([01/01/2011])PermalinkUsing clustering methods in geospatial information systems / X. Wang in Geomatica, vol 64 n° 3 (September 2010)PermalinkSegmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds / A. Sampath in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)PermalinkAutomatic cluster identification for environnemental applications using the self-organizing maps and a new genetic algorithm / T. Oyana in Geocarto international, vol 25 n° 1 (February 2010)PermalinkUsing building permits to monitor disaster recovery: a spatio-temporal case study of coastal Mississipi following hurricane Katrina / J. Stevenson in Cartography and Geographic Information Science, vol 37 n° 1 (January 2010)PermalinkUtilisation de sites Web, (Wikipedia, Flickr, Google) pour caractériser des objets géographiques / Léa Massiot (2010)PermalinkResearch on urban influence domains in China / Shunlin Liang in International journal of geographical information science IJGIS, vol 23 n°11-12 (november 2009)PermalinkStylistic diversity in European state 1: 50 000 topographic maps / Alexander J. 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Chen in Cartography and Geographic Information Science, vol 35 n° 1 (January 2008)PermalinkSpatial aspects of MRSA epidemiology: a case study using stochastic simulation, kernel estimation and SaTScan / Lucy Bastin in International journal of geographical information science IJGIS, vol 21 n° 6-7 (july 2007)PermalinkEvaluating the uncertainty caused by Post Office Box addresses in environmental health studies: A restricted Monte Carlo approach / X. Shi in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)PermalinkNET-DBSCAN: clustering the nodes of a dynamic linear network / Emmanuel Stefanakis in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)PermalinkDEM resolution dependencies of terrain attributes across a landscape / Y. Deng in International journal of geographical information science IJGIS, vol 21 n° 1-2 (january 2007)PermalinkEtude sur la généralisation automatique des carrefours routiers complexes / Jérémy Renard (2007)PermalinkFast cluster polygonization and its applications in data-rich environments / I. Lee in Geoinformatica, vol 10 n° 4 (December 2006)PermalinkAgent-based modelling of shifting cultivation field patterns, Vietnam / M.R. Jepsen in International journal of geographical information science IJGIS, vol 20 n° 9 (october 2006)PermalinkPopulation landscape: a geometric approach to studying spatial patterns of the US urban hierarchy / L. Mu in International journal of geographical information science IJGIS, vol 20 n° 6 (july 2006)PermalinkSegmentation of airborne laser scanning data using a slope adaptative neighbourhood / S. 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