05908nam 2201489z- 450 991055774790332120231214133058.0(CKB)5400000000045863(oapen)https://directory.doabooks.org/handle/20.500.12854/76425(EXLCZ)99540000000004586320202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAdvanced Deep Learning Strategies for the Analysis of Remote Sensing ImagesBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 electronic resource (438 p.)3-0365-0986-0 3-0365-0987-9 The rapid growth of the world population has resulted in an exponential expansion of both urban and agricultural areas. Identifying and managing such earthly changes in an automatic way poses a worth-addressing challenge, in which remote sensing technology can have a fundamental role to answer—at least partially—such demands. The recent advent of cutting-edge processing facilities has fostered the adoption of deep learning architectures owing to their generalization capabilities. In this respect, it seems evident that the pace of deep learning in the remote sensing domain remains somewhat lagging behind that of its computer vision counterpart. This is due to the scarce availability of ground truth information in comparison with other computer vision domains. In this book, we aim at advancing the state of the art in linking deep learning methodologies with remote sensing image processing by collecting 20 contributions from different worldwide scientists and laboratories. The book presents a wide range of methodological advancements in the deep learning field that come with different applications in the remote sensing landscape such as wildfire and postdisaster damage detection, urban forest mapping, vine disease and pavement marking detection, desert road mapping, road and building outline extraction, vehicle and vessel detection, water identification, and text-to-image matching.Research & information: generalbicsscsynthetic aperture radardespecklingmulti-scaleLSTMsub-pixelhigh-resolution remote sensing imageryroad extractionmachine learningDenseUNetscene classificationlifting schemeconvolutionCNNimage classificationdeep featureshand-crafted featuresSinkhorn lossremote sensingtext image matchingtriplet networksEfficientNetsLSTM networkconvolutional neural networkwater identificationwater indexsemantic segmentationhigh-resolution remote sensing imagepixel-wise classificationresult correctionconditional random field (CRF)satelliteobject detectionneural networkssingle-shotdeep learningglobal convolution networkfeature fusiondepthwise atrous convolutionhigh-resolution representationsISPRS vaihingenLandsat-8faster region-based convolutional neural network (FRCNN)single-shot multibox detector (SSD)super-resolutionremote sensing imageryedge enhancementsatellitesopen-set domain adaptationadversarial learningmin-max entropypareto rankingSARSentinel–1Open Street MapU–Netdesertroadinfrastructuremappingmonitoringdeep convolutional networksoutline extractionmisalignmentsnearest feature selectorhyperspectral image classificationtwo stream residual networkBatch Normalizationplant disease detectionprecision agricultureUAV multispectral imagesorthophotos registration3D informationorthophotos segmentationwildfire detectionconvolutional neural networksdensenetgenerative adversarial networksCycleGANdata augmentationpavement markingsvisibilityframeworkurban forestsOUDN algorithmobject-basedhigh spatial resolution remote sensingGenerative Adversarial Networkspost-disasterbuilding damage assessmentanomaly detectionUnmanned Aerial Vehicles (UAV)xBDfeature engineeringorthophotounsupervised segmentationResearch & information: generalBazi Yakoubedt1327926Pasolli EdoardoedtBazi YakoubothPasolli EdoardoothBOOK9910557747903321Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images3038285UNINA03287 am 2200721 n 450 991049577580332120240104030452.02-7574-2927-210.4000/books.septentrion.78071(CKB)4100000010138543(FrMaCLE)OB-septentrion-78071(PPN)242887155(EXLCZ)99410000001013854320200130j|||||||| ||| 0freuu||||||m||||Femmes catholiques, femmes engagéesFrance, Belgique, Angleterre - xxe siècleBruno Duriez, Olivier Rota, Catherine VialleVilleneuve d'AscqPresses universitaires du Septentrion20201 online resource (208 p.) 2-7574-2859-4 L’engagement des femmes catholiques dans l’institution ecclésiale a conduit, au xxe siècle, à bouleverser les représentations admises des rôles féminins dans l’Église. Puisant dans leur foi chrétienne la source de leur action, ces femmes ont dû répondre aux questions suscitées par leurs contacts avec les mouvements féministes, suffragistes ou syndicalistes de leur époque. Consacrées à des situations variées, révélatrices de la pluralité des engagements, les différentes contributions rassemblées ici entendent participer au mouvement de croisement, déjà engagé dans les sciences sociales, entre l’histoire des religions et les études de genre. Il permet d’éclairer les situations, notamment conflictuelles, engendrées par l’engagement féminin dans une institution caractérisée par ses structures hiérarchiques masculines et une longue histoire de pouvoir masculin. The commitment of Roman Catholic women to the ecclesial institution led during the 20th century to an upheaval within conventional representations of feminine roles in the Church.Religionligue féminineféminisme chrétienfemme catholiquereligieusepouvoir religieuxcatholicismeÉgliseengagementféminismeapostolatReligionligue féminineféminisme chrétienfemme catholiquereligieusepouvoir religieuxcatholicismeÉgliseengagementféminismeapostolatBorras Alphonse728269Cacheux Denise1306434Della Sudda Magali1316675Dermenjian Geneviève408735Dewerdt Raymond1453955Dumons Bruno1288723Duriez Bruno1316734Loiseau Dominique1293657Maillard Françoise1453956Paisant Chantal1453957Rota Andreea1453958Rota Olivier1243302Van Osselaer Tine1453959Vialle Catherine1453960Willemetz Nathalie1453961FR-FrMaCLEBOOK9910495775803321Femmes catholiques, femmes engagées3656733UNINA