Advances in Hyperspectral Data Exploitation |
Autore | Chang Chein-I |
Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
Descrizione fisica | 1 electronic resource (434 p.) |
Soggetto topico |
Technology: general issues
History of engineering & technology |
Soggetto non controllato |
hyperspectral image few-shot classification
deep learning meta-learning relation network convolutional neural network constrained-target optimal index factor band selection (CTOIFBS) hyperspectral image underwater spectral imaging system underwater hyperspectral target detection band selection (BS) constrained energy minimization (CEM) lightweight convolutional neural networks hyperspectral imagery classification transfer learning air temperature spatial measurement FTIR MWIR carbon dioxide absorption target detection coffee beans insect damage hyperspectral imaging band selection visualization color formation models multispectral image image fusion joint tensor decomposition anomaly detection constrained sparse representation hyperspectral imagery moving target detection spatio-temporal processing hyperspectral remote sensing image classification constraint representation superpixel segmentation multiscale decision fusion plug-and-play denoising nonlinear unmixing spectral reconstruction residual augmented attentional u-shape network spatial augmented attention channel augmented attention boundary-aware constraint atmospheric transmittance temperature emissivity separation midwave infrared hyperspectral images hyperspectral image super-resolution data fusion spectral-spatial residual network self-supervised training hyperspectral vegetation generative adversarial network data augmentation classification rice leaf blast hyperspectral imaging data deep convolutional neural networks fused features evolutionary computation heuristic algorithms machine learning unmanned aerial vehicles (UAVs) vegetation mapping upland swamps mine environment rice rice leaf folder hyperspectral image classification change detection self-supervised learning attention mechanism multi-source image fusion SFIM least square estimation spatial filter hyperspectral imaging (HSI) hyperspectral target detection hyperspectral reconstruction hyperspectral unmixing |
ISBN | 3-0365-5796-2 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910637782203321 |
Chang Chein-I | ||
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Hyperspectral Remote Sensing of Agriculture and Vegetation |
Autore | Pascucci Simone |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
Descrizione fisica | 1 electronic resource (266 p.) |
Soggetto topico |
Research & information: general
Environmental economics |
Soggetto non controllato |
hyperspectral LiDAR
Red Edge AOTF vegetation parameters leaf chlorophyll content DLARI MDATT adaxial abaxial spectral reflectance peanut field spectroscopy hyperspectral heavy metals grapevine PLS SVM MLR multi-angle observation hyperspectral remote sensing BRDF vegetation classification object-oriented segmentation spectroscopy artificial intelligence proximal sensing data precision agriculture spectra vegetation plant classification discrimination feature selection waveband selection support vector machine random forest Natura 2000 invasive species expansive species biodiversity proximal sensor macronutrient micronutrient remote sensing hyperspectral imaging platforms and sensors analytical methods crop properties soil characteristics classification of agricultural features canopy spectra chlorophyll content continuous wavelet transform (CWT) correlation coefficient partial least square regression (PLSR) reproducibility replicability partial least squares Ethiopia Eragrostis tef hyperspectral remote sensing for soil and crops in agriculture hyperspectral imaging for vegetation plant traits high-resolution spectroscopy for agricultural soils and vegetation hyperspectral databases for agricultural soils and vegetation hyperspectral data as input for modelling soil, crop, and vegetation product validation new hyperspectral technologies future hyperspectral missions |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557691803321 |
Pascucci Simone | ||
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Learning to Understand Remote Sensing Images . Volume 2 |
Autore | Wang Qi |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica | 1 electronic resource (363 pages) |
Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
ISBN | 3-03897-699-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910367755503321 |
Wang Qi | ||
MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Learning to Understand Remote Sensing Images . Volume 1 |
Autore | Wang Qi |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica | 1 electronic resource (414 pages) |
Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
ISBN | 3-03897-685-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910367755603321 |
Wang Qi | ||
MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Volcanic Plumes.Impacts on the Atmosphere and Insights into Volcanic Processes |
Autore | McGonigle Andrew (Volcanologist) |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica | 1 electronic resource (252 p.) |
Soggetto non controllato |
radioactive disequilibria 210Pb-210Bi-210Po
volcanic geochemistry radiative transfer spherical-cap bubble plume satellite remote sensing portable photometry puffing Holuhraun interdisciplinary volcanology gas slug atmospheric remote sensing analysis software gases image processing remote sensing SEVIRI data oxygen and sulfur multi-isotopes nonlinear spectral unmixing UV cameras ultraviolet cameras cloud height atmospheric chemistry Python 2.7 degassing processes volcanic plumes fissure eruption radiative forcing basaltic volcanism volcanic plume top height O3 eruption start and duration Differential Absorption Lidar (DIAL) volcanic emissions volcanology volcanic CO2 flux volcanic aerosols 2011-2015 Etna lava fountains SO2 reactive halogen nonlinear PCA gas Etna volcano geochemical modelling BrO volcanic sulfate aerosols volcanic gases SSA hyperspectral remote sensing time averaged discharge rate eruption monitoring Bárðarbunga strombolian aerosol optical properties Mount Etna Taylor bubble |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910346847103321 |
McGonigle Andrew (Volcanologist) | ||
MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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