top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.
Advances in Hyperspectral Data Exploitation
Advances in Hyperspectral Data Exploitation
Autore Chang Chein-I
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 online resource (434 p.)
Soggetto topico History of engineering & technology
Technology: general issues
Soggetto non controllato air temperature
anomaly detection
atmospheric transmittance
attention mechanism
band selection
band selection (BS)
boundary-aware constraint
carbon dioxide absorption
change detection
channel augmented attention
classification
coffee beans
color formation models
constrained energy minimization (CEM)
constrained sparse representation
constrained-target optimal index factor band selection (CTOIFBS)
constraint representation
convolutional neural network
data augmentation
data fusion
deep convolutional neural networks
deep learning
denoising
emissivity
evolutionary computation
FTIR
fused features
generative adversarial network
heuristic algorithms
hyperspectral
hyperspectral image
hyperspectral image classification
hyperspectral image few-shot classification
hyperspectral image super-resolution
hyperspectral imagery
hyperspectral imagery classification
hyperspectral images
hyperspectral imaging
hyperspectral imaging (HSI)
hyperspectral imaging data
hyperspectral reconstruction
hyperspectral remote sensing
hyperspectral target detection
hyperspectral unmixing
image classification
image fusion
insect damage
joint tensor decomposition
least square estimation
lightweight convolutional neural networks
machine learning
meta-learning
midwave infrared
mine environment
moving target detection
multi-source image fusion
multiscale decision fusion
multispectral image
MWIR
nonlinear unmixing
plug-and-play
relation network
residual augmented attentional u-shape network
rice
rice leaf blast
rice leaf folder
self-supervised learning
self-supervised training
separation
SFIM
spatial augmented attention
spatial filter
spatial measurement
spatio-temporal processing
spectral reconstruction
spectral-spatial residual network
superpixel segmentation
target detection
temperature
transfer learning
underwater hyperspectral target detection
underwater spectral imaging system
unmanned aerial vehicles (UAVs)
upland swamps
vegetation
vegetation mapping
visualization
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
Opac: Controlla la disponibilità qui
Research in Metabolomics via Nuclear Magnetic Resonance Spectroscopy: Data Mining, Biochemistry and Clinical Chemistry
Research in Metabolomics via Nuclear Magnetic Resonance Spectroscopy: Data Mining, Biochemistry and Clinical Chemistry
Autore Vignoli Alessia
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 online resource (136 p.)
Soggetto topico Biochemistry
Biology, life sciences
Research and information: general
Soggetto non controllato artificial intelligence
biomarkers
clustering
coffee beans
coffee processing
coffee varieties
colorectal cancer
COVID-19
deep learning
EOS
exhaled breath condensate
health science
human plasma
LOS
machine learning
metabolomics
n/a
nanoparticles exposure
neonatal sepsis
NMR
NMR metabolomics
NMR spectroscopy
nuclear magnetic resonance
nuclear magnetic resonance spectroscopy
phenotyping
post-harvest treatment
preterm birth
relapse
surgery
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Research in Metabolomics via Nuclear Magnetic Resonance Spectroscopy
Record Nr. UNINA-9910585936303321
Vignoli Alessia  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui