Learning to Understand Remote Sensing Images

With 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 remot...

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Bibliographic Details
Format:	eBook
Language:	English
Published:	MDPI - Multidisciplinary Digital Publishing Institute 2019
Subjects:	Computer science 1-dimensional (1-D) adaptive convolutional kernels aerial image aerial images anti-noise transfer network automatic cluster number determination building damage detection canonical correlation weighted voting change feature analysis class imbalance classification climate change CNN color matching compressive sensing conditional random fields conservation convolution neural network convolutional neural network convolutional neural network (CNN) Convolutional Neural Network (CNN) convolutional neural networks deep convolutional neural networks deep learning deep salient feature despeckling dictionary learning dilated convolution dimensionality expansion dimensionality reduction downscaling DSFATN endmember extraction energy distribution optimizing ensemble learning feature extraction feature matching flood fully convolutional network fully convolutional network (FCN) fuzzy neural network Fuzzy-GA decision making system gate geo-referencing GeoEye-1 geostationary satellite remote sensing image GF-4 PMS GSHHG database hard classification hashing heterogeneous domain adaptation high resolution high resolution image HJ-1A/B CCD Hough transform hyperedge weight estimation hypergraph learning hyperparameter sparse representation hyperspectral image hyperspectral image classification hyperspectral imagery hyperspectral remote sensing ice concentration image alignment image classification image fusion image registration image segmentation infrared image inundation mapping ISPRS kernel method land cover land cover change land surface temperature land use Landsat Landsat imagery linear spectral unmixing locality information machine learning machine learning techniques manifold ranking metadata mixed pixel Modest AdaBoost MODIS morphological profiles MSER multi-objective multi-scale clustering multi-seasonal multi-sensor multi-sensor image matching multi-task learning multi-view canonical correlation analysis ensemble multiscale representation multispectral imagery multispectral images nonlinear classification object-based object-based image analysis online learning optical remotely sensed images optical sensors optimal transport optimized kernel minimum noise fraction (OKMNF) particle swarm optimization phase congruency quality assessment Radon transform Random Forests (RF) ratio images regional land cover remote sensing remote sensing image correction remote sensing image retrieval residual learning road detection road segmentation ROI detection saliency analysis saliency detection SAR image SAR imagery satellite images scene classification sea-land segmentation Segment-Tree Filtering segmentation SELF semantic labeling semantic segmentation semi-supervised learning sensitivity analysis ship detection Siamese neural network single stream optimization skip connection sparse and low-rank graph sparse representation spatial attraction model (SAM) spatial distribution spatiotemporal context learning speckle speckle filters structured sparsity sub-pixel sub-pixel change detection subpixel mapping (SPM) Support Vector Machine (SVM) SVMs synthetic aperture radar Synthetic Aperture Radar (SAR) target detection tensor tensor low-rank approximation tensor sparse decomposition TensorFlow texture analysis THEOS threshold stability topic modelling transfer learning UAV unsupervised classification urban heat island urban surface water extraction vehicle classification vehicle localization very high resolution (VHR) satellite image very high resolution images visible light and infrared integrated camera wavelet transform
Online Access:	Open Access: DOAB: description of the publication Open Access: DOAB, download the publication