LEADER 08643nam 2202377z- 450 001 9910367755503321 005 20231214133541.0 010 $a3-03897-699-7 035 $a(CKB)4100000010106162 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/51489 035 $a(EXLCZ)994100000010106162 100 $a20202102d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLearning to Understand Remote Sensing Images$hVolume 2 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 215 $a1 electronic resource (363 pages) 311 $a3-03897-698-9 330 $aWith the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field. 610 $ametadata 610 $aimage classification 610 $asensitivity analysis 610 $aROI detection 610 $aresidual learning 610 $aimage alignment 610 $aadaptive convolutional kernels 610 $aHough transform 610 $aclass imbalance 610 $aland surface temperature 610 $ainundation mapping 610 $amultiscale representation 610 $aobject-based 610 $aconvolutional neural networks 610 $ascene classification 610 $amorphological profiles 610 $ahyperedge weight estimation 610 $ahyperparameter sparse representation 610 $asemantic segmentation 610 $avehicle classification 610 $aflood 610 $aLandsat imagery 610 $atarget detection 610 $amulti-sensor 610 $abuilding damage detection 610 $aoptimized kernel minimum noise fraction (OKMNF) 610 $asea-land segmentation 610 $anonlinear classification 610 $aland use 610 $aSAR imagery 610 $aanti-noise transfer network 610 $asub-pixel change detection 610 $aRadon transform 610 $asegmentation 610 $aremote sensing image retrieval 610 $aTensorFlow 610 $aconvolutional neural network 610 $aparticle swarm optimization 610 $aoptical sensors 610 $amachine learning 610 $amixed pixel 610 $aoptical remotely sensed images 610 $aobject-based image analysis 610 $avery high resolution images 610 $asingle stream optimization 610 $aship detection 610 $aice concentration 610 $aonline learning 610 $amanifold ranking 610 $adictionary learning 610 $aurban surface water extraction 610 $asaliency detection 610 $aspatial attraction model (SAM) 610 $aquality assessment 610 $aFuzzy-GA decision making system 610 $aland cover change 610 $amulti-view canonical correlation analysis ensemble 610 $aland cover 610 $asemantic labeling 610 $asparse representation 610 $adimensionality expansion 610 $aspeckle filters 610 $ahyperspectral imagery 610 $afully convolutional network 610 $ainfrared image 610 $aSiamese neural network 610 $aRandom Forests (RF) 610 $afeature matching 610 $acolor matching 610 $ageostationary satellite remote sensing image 610 $achange feature analysis 610 $aroad detection 610 $adeep learning 610 $aaerial images 610 $aimage segmentation 610 $aaerial image 610 $amulti-sensor image matching 610 $aHJ-1A/B CCD 610 $aendmember extraction 610 $ahigh resolution 610 $amulti-scale clustering 610 $aheterogeneous domain adaptation 610 $ahard classification 610 $aregional land cover 610 $ahypergraph learning 610 $aautomatic cluster number determination 610 $adilated convolution 610 $aMSER 610 $asemi-supervised learning 610 $agate 610 $aSynthetic Aperture Radar (SAR) 610 $adownscaling 610 $aconditional random fields 610 $aurban heat island 610 $ahyperspectral image 610 $aremote sensing image correction 610 $askip connection 610 $aISPRS 610 $aspatial distribution 610 $ageo-referencing 610 $aSupport Vector Machine (SVM) 610 $avery high resolution (VHR) satellite image 610 $aclassification 610 $aensemble learning 610 $asynthetic aperture radar 610 $aconservation 610 $aconvolutional neural network (CNN) 610 $aTHEOS 610 $avisible light and infrared integrated camera 610 $avehicle localization 610 $astructured sparsity 610 $atexture analysis 610 $aDSFATN 610 $aCNN 610 $aimage registration 610 $aUAV 610 $aunsupervised classification 610 $aSVMs 610 $aSAR image 610 $afuzzy neural network 610 $adimensionality reduction 610 $aGeoEye-1 610 $afeature extraction 610 $asub-pixel 610 $aenergy distribution optimizing 610 $asaliency analysis 610 $adeep convolutional neural networks 610 $asparse and low-rank graph 610 $ahyperspectral remote sensing 610 $atensor low-rank approximation 610 $aoptimal transport 610 $aSELF 610 $aspatiotemporal context learning 610 $aModest AdaBoost 610 $atopic modelling 610 $amulti-seasonal 610 $aSegment-Tree Filtering 610 $alocality information 610 $aGF-4 PMS 610 $aimage fusion 610 $awavelet transform 610 $ahashing 610 $amachine learning techniques 610 $asatellite images 610 $aclimate change 610 $aroad segmentation 610 $aremote sensing 610 $atensor sparse decomposition 610 $aConvolutional Neural Network (CNN) 610 $amulti-task learning 610 $adeep salient feature 610 $aspeckle 610 $acanonical correlation weighted voting 610 $afully convolutional network (FCN) 610 $adespeckling 610 $amultispectral imagery 610 $aratio images 610 $alinear spectral unmixing 610 $ahyperspectral image classification 610 $amultispectral images 610 $ahigh resolution image 610 $amulti-objective 610 $aconvolution neural network 610 $atransfer learning 610 $a1-dimensional (1-D) 610 $athreshold stability 610 $aLandsat 610 $akernel method 610 $aphase congruency 610 $asubpixel mapping (SPM) 610 $atensor 610 $aMODIS 610 $aGSHHG database 610 $acompressive sensing 700 $aWang$b Qi$4auth$0646598 906 $aBOOK 912 $a9910367755503321 996 $aLearning to Understand Remote Sensing Images$93024026 997 $aUNINA