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Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement
Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement
Autore Kobayashi Hirokazu
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 online resource (570 p.)
Soggetto topico History of engineering and technology
Soggetto non controllato 2-D PPS
3-D deformation
adaptive reduced method
aircraft surveillance
altitude measurement accuracy
analytical approach
antenna array
atomic norm
automatic guided vehicle
Bayesian inversion
bistatic inverse synthetic aperture radar
bistatic MIMO radar
block coherence measure
block sparse Bayesian learning
CLEAN technique
clustering methods
clutter reduction
clutter suppression
coherent integration
coherent pulse trains
comprehensive SAR
conductivity
constant modulus sequences
constitutive parameters
contrast target detection
correlation properties
Cramer-Rao lower bound
critical height
crosshole ground penetrating radar (GPR)
curved orbit
deception jamming
dechirping
denoising detection
deramping-based approach
differential SAR tomography
dilation morphology
direct position determination
discrete cosine transform (DCT)
discrete scatterer model
DOA estimation
DoA/DoD estimation
DOD/DOA estimation
Doppler
Doppler rate
doppler tolerance
double negative
dual-band
dual-polarized radar
electromagnetic wave attribute
energy spectrum method
entropy thresholding
FMCW radio altimeter
forward model
fractional Fourier transform (FRFT)
frequency shifting modulation
generative adversarial nets
generator and discriminator
GPR
guided filter
height pulses
high reliability
high switching speed
hyperbolic tangent function
image fusion
image processing
integral cubic phase function (ICPF)
interrupted sampling
interrupted transmitting and receiving (ITR)
inverse synthetic aperture ladar (ISAL)
inverse synthetic aperture radar (ISAR)
ISAR
K-L transform
least square error
linear geometry distortion
local correlation
local gradient method
low control voltage
low-rank approximation
lunar penetrating radar
man-made targets
maneuvering target
maneuvering target detection
marine radar
maritime traffic monitoring
Markov chain Monte Carlo (MCMC)
maximum likelihood estimator
metamaterial absorber
methodological error
micro-Doppler
micro-motion feature extraction
microwave imaging
MIMO radar
modeling error
motion parameter estimation
multiparametric SAR observation
multipath ghost suppression
mutual coupling
n/a
narrowband interference separation
non-uniform fast Fourier transform (NUFFT)
non-uniform grid
off-grid sparse problem
orthogonal matching pursuit
parameter estimation
passive bistatic radar
PBR (passive bistatic radar)
permittivity
phased array radar
polarimetric decomposition
prior information
pulse radar
radar echo cancellation
radar jamming
radon transform
relative water content
remote sensing
RF MEMS
rotating target
S-transformation
saliency detection
saliency preprocessing LLC
SAR
scene classification
seasonal permafrost
second-order phase difference (SoPD)
seislet transform
sensing matrix optimization
series reversion
simultaneous polarimetric radar
single moving sensor
singular value decomposition (SVD)
small wind streak
SNR
spaceborne
sparse recovery
sparse representation
speckle noise filtering
squinted SAR
subspace extraction
switch
synchrosqueezing
synthetic aperture radar
synthetic aperture radar (SAR)
Synthetic Aperture Radar (SAR)
through-wall imaging
through-wall radar imaging
time-frequency analysis
tomography
ultra-wide frequency deviation
ultrahigh resolution
unmanned aerial vehicle
wake detection and analysis
wideband noise interference
wind direction retrieval
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557305803321
Kobayashi Hirokazu  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang
Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang
Autore Wang Qi
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (414 pages)
Soggetto topico Computer science
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 9783038976851
3038976857
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
Opac: Controlla la disponibilità qui
Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang
Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang
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 9783038976998
3038976997
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
Opac: Controlla la disponibilità qui
Statistical Machine Learning for Human Behaviour Analysis
Statistical Machine Learning for Human Behaviour Analysis
Autore Moeslund Thomas
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 online resource (300 p.)
Soggetto topico History of engineering and technology
Soggetto non controllato 3D convolutional neural networks
accuracy
action recognition
adaptive classifiers
age classification
attention allocation
attention behavior
biometric recognition
blurring detection
body movements
boundary segmentation
categorical data
committee of classifiers
concept drift
context-aware framework
convolutional neural network
deep learning
discrete stationary wavelet transform
emotion recognition
Empatica E4
ensemble methods
face analysis
face segmentation
false negative rate
fibromyalgia
fingerprint image enhancement
fingerprint quality
foggy image
frequency domain
gait event
gender classification
gestures
hand sign language
head pose estimation
hybrid entropy
individual behavior estimation
information entropy
interpretable machine learning
k-means clustering
Kinect sensor
Learning Using Concave and Convex Kernels
multi-modal
multi-objective evolutionary algorithms
multimodal-based human identification
neural networks
noisy image
object contour detection
privacy
privacy-aware
profoundly deaf
recurrent concepts
restricted Boltzmann machine (RBM)
rule-based classifiers
saliency detection
self-reported survey
silhouettes difference
single pixel single photon image acquisition
singular point detection
spatial domain
spectrograms
speech
speech emotion recognition
statistical-based time-frequency domain and crowd condition
stock price direction prediction
time-of-flight
toe-off detection
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557288403321
Moeslund Thomas  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui