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Digital Signal, Image and Video Processing for Emerging Multimedia Technology
Digital Signal, Image and Video Processing for Emerging Multimedia Technology
Autore Kim Byung-Gyu
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (392 p.)
Soggetto topico History of engineering & technology
Soggetto non controllato closed circuit television (CCTV)
character order preserving
cloud system
privacy risk
security
video surveillance
3D
depth map
inter-component prediction
MVD
reversible data hiding
texture
wavelet analysis
deep learning
super-resolution
deep neural architecture
pattern mining
multi-scale analysis
reversible data hiding (RDH)
image processing
cloud computing
public key cryptography (PKC)
classification
content-based image retrieval
genetic algorithms
image retrieval
image classification
Wiener-Granger causality
block-compressive sensing (BCS)
saliency
error analysis
flexible partitioning
step-less adaptive sampling
non-linear filters
MCV and MLV filters
de-noising
noise removal
edge preserving
video coding
motion estimation
motion compensation
affine motion model
perspective motion model
VVC
quantization (signal)
channel allocation
scalable video coding
convolution neural network
scene recognition
vector of locally aggregated descriptor
weakly supervised attention map
fire and smoke detection
spatial and temporal
wavelet transform
coefficient of variation
image steganalysis
WOW
UNIWARD
ternary classification
convolutional neural network (CNN)
bayesian optimization
gaussian process
learning rate
acauisition function
machine learning
moving object
image stabilization
object detection
optical flow
surveillance
UAVs
multiview high efficiency video coding
ρ model
bit allocation
rate control
image similarity
frame complexity
image deblurring
generative adversarial network
Wasserstein distance
adversarial loss
perceptual loss
sentiment analysis
social media
lexicon
image fusion
multi-focus
trimaps
focus maps
VisDrone2019
aerial imagery
Faster R-CNN
SSD
RFCN
YOLOv3
RetinaNet
SNIPER
CenterNet
wrist-mounted DiverPAD
electrical insulator
capacitive touchscreen
marine leisure activities
convolutional neural networks
pattern recognition
low light
image restoration
denoise
noise reduction
deep leaning
multiple feature
dependency detection
surveillance system
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557136003321
Kim Byung-Gyu  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
UAVs for Vegetation Monitoring
UAVs for Vegetation Monitoring
Autore de Castro Megías Ana
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (452 p.)
Soggetto topico Research & information: general
Soggetto non controllato UAS
UAV
vegetation cover
multispectral
land cover
forest
Acacia
Indonesia
tropics
vegetation ground cover
vegetation indices
agro-environmental measures
olive groves
southern Spain
sUAS
water stress
ornamental
container-grown
artificial intelligence
machine learning
deep learning
neural network
visual recognition
precision agriculture
canopy cover
image analysis
crop mapping
evapotranspiration (ET)
GRAPEX
remote sensing
Two Source Energy Balance model (TSEB)
contextual spatial domain/resolution
data aggregation
eddy covariance (EC)
Fusarium wilt
crop disease
banana
multispectral remote sensing
purple rapeseed leaves
unmanned aerial vehicle
U-Net
plant segmentation
nitrogen stress
Glycine max
RGB
canopy height
close remote sensing
growth model
curve fitting
NDVI
solar zenith angle
flight altitude
time of day
operating parameters
CNN
Faster RCNN
SSD
Inception v2
patch-based CNN
MobileNet v2
detection performance
inference time
disease detection
cotton root rot
plant-level
single-plant
plant-by-plant
classification
UAV remote sensing
crop monitoring
RGB imagery
multispectral imagery
century-old biochar
semantic segmentation
random forest
crop canopy
multispectral image
chlorophyll content
remote sensing technique
individual plant segmentation
plant detection
transfer learning
maize tassel
tassel branch number
convolution neural network
VGG16
plant nitrogen estimation
vegetation index
image segmentation
transpiration
method comparison
oil palm
multiple linear regression
support vector machine
artificial neural network
UAV hyperspectral
wheat yellow rust
disease monitoring
texture
spatial resolution
RGB camera
thermal camera
drought tolerance
forage grass
HSV
CIELab
broad-sense heritability
phenotyping gap
high throughput field phenotyping
UAV digital images
winter wheat biomass
multiscale textures
red-edge spectra
least squares support vector machine
variable importance
drone
hyperspectral
thermal
nutrient deficiency
weed detection
disease diagnosis
plant trails
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557661103321
de Castro Megías Ana  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui