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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historical document analysis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
Advances in Remote Sensing for Global Forest Monitoring
Advances in Remote Sensing for Global Forest Monitoring
Autore Tomppo Erkki
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (352 p.)
Soggetto topico Research & information: general
Environmental economics
Soggetto non controllato forest structure change
EBLUP
small area estimation
multitemporal LiDAR and stand-level estimates
forest cover
Sentinel-1
Sentinel-2
data fusion
machine-learning
Germany
South Africa
temperate forest
savanna
classification
Sentinel 2
land use land cover
improved k-NN
logistic regression
random forest
support vector machine
statistical estimator
IPCC good practice guidelines
activity data
emissions factor
removals factor
Picea crassifolia Kom
compatible equation
nonlinear seemingly unrelated regression
error-in-variable modeling
leave-one-out cross-validation
digital surface model
digital terrain model
canopy height model
constrained neighbor interpolation
ordinary neighbor interpolation
point cloud density
stereo imagery
remotely sensed LAI
field measured LAI
validation
magnitude
uncertainty
temporal dynamics
state space models
forest disturbance mapping
near real-time monitoring
CUSUM
NRT monitoring
deforestation
degradation
tropical forest
tropical peat
forest type
deep learning
FCN8s
CRFasRNN
GF2
dual-FCN8s
random forests
error propagation
bootstrapping
Landsat
LiDAR
La Rioja
forest area change
data assessment
uncertainty evaluation
inconsistency
forest monitoring
drought
time series satellite data
Bowen ratio
carbon flux
boreal forest
windstorm damage
synthetic aperture radar
C-band
genetic algorithm
multinomial logistic regression
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557338103321
Tomppo Erkki  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Geography Education Promoting Sustainability
Geography Education Promoting Sustainability
Autore Jeronen Eila
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 electronic resource (180 p.)
Soggetto non controllato teaching competencies
environmental education
digital tools
issues of scale
landscape drawings and texts
mental models
evaluation
systems thinking
ecology education
preconceptions
geographical education
Sustainable Development Goals
climate change
mapping
mixed methods
geography education
critical pedagogy
TPACK
K-12 education
literature review
professional development
sustainability
radical environmentalism
case study
alternative conceptions
experiences connected to environment
environmental relationship
quality of life
dialogic teaching
education for sustainable development (ESD)
data mining
education for sustainable development
place-based education
students
ecopedagogy
general education
magnitude
environmental approach
misconceptions
collective evaluation
environmental values
epistemological beliefs
school project
gender equality
higher education
qualitative study
outdoor education
democracy
international collaboration
inductive content analysis
environment
collaboration
sustainability education
Spatial Data Infrastructures
conceptual change
landscape
ISBN 3-03928-501-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910404089503321
Jeronen Eila  
MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui