Advanced Machine Learning and Deep Learning Approaches for Remote Sensing II

This publication elucidates the application of advanced technologies, including machine learning and deep learning, rooted in artificial intelligence, to the realm of remote sensing. It delineates the methodology employed to address prevailing challenges associated with the processing of images and...

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Bibliografiska uppgifter
Materialtyp:	Online
Språk:	engelska
Utgiven:	MDPI - Multidisciplinary Digital Publishing Institute 2024
Ämnen:	hyperspectral image (HSI) classification transformer convolutional neural network (CNN) Sequencer long short-term memory network (LSTM) remote sensing object detection point representation sample quality assessment aerial target recognition center-ness quality radar echo extrapolation sequence-to-sequence (Seq2Seq) network 3D-Unet convective nowcasting hyperspectral unmixing spectral–spatial attention mechanism deep learning autoencoder moving point target low SNR transient disturbance temporal profile skip connection shifted window spatial feature extraction (SFE) spatial position encoding (SPE) geostatistical modeling multiple-point statistics uncertainty quantification subglacial topographic model hydrological model wildfire detection generative machine-learning stochastic modeling remote sensing segmentation uncertainty analysis deep neural network adversarial defense deep ensemble model unmanned aerial vehicle image recognition hyperspectral images classification network pruning multi-task optimization knowledge transfer multi-objective optimization 2D DOA estimation low-elevation-angle targets L-shaped uniform array L-shaped sparse array dilated convolutional autoencoder dilated convolutional neural network 3D convolution spatiotemporal fusion machine learning multi-source precipitation ConvLSTM F-SVD ionosphere peak height of F2 layer hmF2 prediction data sensor fusion extended Kalman filter lidar radar super-resolution remote sensing image convolutional neural network self-similarity gated recurrent unit ecological service value ecological–economic harmony driving mechanism thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
Länkar:	ONIX_20240514_9783725807710_454
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ONIX_20240514_9783725807710_454

Advanced Machine Learning and Deep Learning Approaches for Remote Sensing II

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