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Advances in Image Processing, Analysis and Recognition Technology
Advances in Image Processing, Analysis and Recognition Technology
Autore Frejlichowski Dariusz
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (386 p.)
Soggetto topico Information technology industries
Computer science
Soggetto non controllato CIELab
component Substitution
Pan sharpening
Pléiades VHR Image
coal
inertinite macerals
classification
multifractal analysis
support vector machine
block-based coding
video coding
H.265/HEVC
affine motion compensation
image registration
homography matrix
local homography transformation
convolutional neural network
moving direct linear transformation
super-resolution (SR)
convolution neural network (CNN)
Gene Expression Programming (GEP)
deep learning
image preclassification
suspicious behavior detection
motion
magnitude
gradient
reactivity
saliency
haze removal
dark channel
atmospheric-light estimation
coarse-to-fine search strategy
sparse dictionary
stable recovery
frame
RIP
local dimming
retinex theory
bi-histogram equalization
contrast ratio
details preservation
pansharpening
image fusion
image quality
Satellite Pour l'Observation de la Terre (SPOT) 6
spectral consistency
spatial consistency
synthesis
artificial intelligence
dental application
images
detection
parseval frame
transform
sparse representation
octave convolution
bilingual scene text reading
Ethiopic script
attention
nasal cytology
automatic cell segmentation
rhinology
image analysis
feature extraction
shape context
plant recognition
DPCNN
BOF
numeral spotting
historical document analysis
convolutional neural networks
deep transfer learning
handwritten digit recognition
spectrum correction
intensity correction
compressed sensing
tradeoff process
IKONOS
remote sensing
fine-tuning
learning rate scheduler
cyclical learning rates
label smoothing
classification accuracy
neural networks
salient object detection
RGB-D
object detection
small object
multi-scale sampling
balanced sampling
texture
structure
optical
coke
iron ore
sinter
image processing
segmentation
identification
action recognition
silhouette sequences
shape features
ambient assisted living
active ageing
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910576879103321
Frejlichowski Dariusz  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
UAV Photogrammetry and Remote Sensing
UAV Photogrammetry and Remote Sensing
Autore Carvajal-Ramírez Fernando
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (257 p.)
Soggetto topico Technology: general issues
Soggetto non controllato unmanned aerial vehicle
urban LULC
GEOBIA
multiscale classification
unmanned aircraft system (UAS)
deep learning
super-resolution (SR)
convolutional neural network (CNN)
generative adversarial network (GAN)
structure-from-motion
photogrammetry
remote sensing
UAV
3D-model
surveying
vertical wall
snow
remotely piloted aircraft systems
structure from motion
lidar
forests
orthophotography
construction planning
sustainable construction
urbanism
BIM
building maintenance
unmanned aerial vehicle (UAV)
structure-from-motion (SfM)
ground control points (GCP)
accuracy assessment
point clouds
corridor mapping
UAV photogrammetry
terrain modeling
vegetation removal
unmanned aerial vehicles
power lines
image-based reconstruction
3D reconstruction
unmanned aerial systems
time series
accuracy
reproducibility
orthomosaic
validation
drone
GNSS RTK
precision
elevation
multispectral imaging
vegetation indices
nutritional analysis
correlation
optimal harvest time
UAV images
monoscopic mapping
stereoscopic plotting
image overlap
optimal image selection
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557781303321
Carvajal-Ramírez Fernando  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui