Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images |
Autore | Bazi Yakoub |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
Descrizione fisica | 1 electronic resource (438 p.) |
Soggetto topico | Research & information: general |
Soggetto non controllato |
synthetic aperture radar
despeckling multi-scale LSTM sub-pixel high-resolution remote sensing imagery road extraction machine learning DenseUNet scene classification lifting scheme convolution CNN image classification deep features hand-crafted features Sinkhorn loss remote sensing text image matching triplet networks EfficientNets LSTM network convolutional neural network water identification water index semantic segmentation high-resolution remote sensing image pixel-wise classification result correction conditional random field (CRF) satellite object detection neural networks single-shot deep learning global convolution network feature fusion depthwise atrous convolution high-resolution representations ISPRS vaihingen Landsat-8 faster region-based convolutional neural network (FRCNN) single-shot multibox detector (SSD) super-resolution remote sensing imagery edge enhancement satellites open-set domain adaptation adversarial learning min-max entropy pareto ranking SAR Sentinel–1 Open Street Map U–Net desert road infrastructure mapping monitoring deep convolutional networks outline extraction misalignments nearest feature selector hyperspectral image classification two stream residual network Batch Normalization plant disease detection precision agriculture UAV multispectral images orthophotos registration 3D information orthophotos segmentation wildfire detection convolutional neural networks densenet generative adversarial networks CycleGAN data augmentation pavement markings visibility framework urban forests OUDN algorithm object-based high spatial resolution remote sensing Generative Adversarial Networks post-disaster building damage assessment anomaly detection Unmanned Aerial Vehicles (UAV) xBD feature engineering orthophoto unsupervised segmentation |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557747903321 |
Bazi Yakoub
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Very High Resolution (VHR) Satellite Imagery: Processing and Applications |
Autore | Marcello Javier |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica | 1 electronic resource (262 p.) |
Soggetto non controllato |
very high-resolution Pléiades imagery
surface convergence data augmentation acquisition geometry SVM classification urban water mapping beaver dam analogue agriculture parcel segmentation morphological building index airborne hypespectral imagery sunglint correction water index over-segmentation index (OSI) High-resolution satellite imagery multi-resolution segmentation (MRS) GaoFen-2 (GF-2) benthic mapping scene classification greenhouse extraction edge constraint Deformable CNN built-up areas extraction ultra-dense connection seagrass beaver mimicry forested mountain natural hazards remote sensing dimensionality reduction techniques road extraction landslide monitoring Slumgullion landslide synthetic aperture radar building detection Worldview-2 saliency index under-segmentation index (USI) texture analysis fast marching method video satellite CNN capsule super-resolution feature distillation shadow detection PrimaryCaps semiautomatic compensation unit superpixels riparian QuickBird submesoscale linear unmixing accuracy assessment composite error index (CEI) cyanobacteria local feature points Faster R-CNN occluded object detection error index of total area (ETA) large displacements threshold stability remote sensing imagery water column correction canopy height model spiral eddy sub-pixel offset tracking consensus stream restoration western Baltic Sea Worldview very high-resolution image CapsNet atmospheric correction |
ISBN | 3-03921-757-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Altri titoli varianti | Very High Resolution |
Record Nr. | UNINA-9910367747503321 |
Marcello Javier
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MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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