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Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images
Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images
Autore Bazi Yakoub
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 online resource (438 p.)
Soggetto topico Research and information: general
Soggetto non controllato 3D information
adversarial learning
anomaly detection
Batch Normalization
building damage assessment
CNN
conditional random field (CRF)
convolution
convolutional neural network
convolutional neural networks
CycleGAN
data augmentation
deep convolutional networks
deep features
deep learning
densenet
DenseUNet
depthwise atrous convolution
desert
despeckling
edge enhancement
EfficientNets
faster region-based convolutional neural network (FRCNN)
feature engineering
feature fusion
framework
generative adversarial networks
Generative Adversarial Networks
global convolution network
hand-crafted features
high spatial resolution remote sensing
high-resolution remote sensing image
high-resolution remote sensing imagery
high-resolution representations
hyperspectral image classification
image classification
infrastructure
ISPRS vaihingen
Landsat-8
lifting scheme
LSTM
LSTM network
machine learning
mapping
min-max entropy
misalignments
monitoring
multi-scale
nearest feature selector
neural networks
object detection
object-based
Open Street Map
open-set domain adaptation
orthophoto
orthophotos registration
orthophotos segmentation
OUDN algorithm
outline extraction
pareto ranking
pavement markings
pixel-wise classification
plant disease detection
post-disaster
precision agriculture
remote sensing
remote sensing imagery
result correction
road
road extraction
SAR
satellite
satellites
scene classification
semantic segmentation
Sentinel-1
single-shot
single-shot multibox detector (SSD)
Sinkhorn loss
sub-pixel
super-resolution
synthetic aperture radar
text image matching
triplet networks
two stream residual network
U-Net
UAV multispectral images
Unmanned Aerial Vehicles (UAV)
unsupervised segmentation
urban forests
visibility
water identification
water index
wildfire detection
xBD
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557747903321
Bazi Yakoub  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Mapping Tree Species Diversity
Mapping Tree Species Diversity
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2023
Descrizione fisica 1 online resource (414 p.)
Soggetto topico Geography
Research & information: general
Soggetto non controllato accuracy
aerial imagery
ALS
AVIRIS-NG
biodiversity
biosecurity
boreal forest
BPWW
classification
climatic gradient
CNN
convex hull volume
convolutional networks
convolutional neural network
cross-validation
curve matching
data fusion
dead wood
deep learning
endangered tree species
feature extraction
forest
forest cover and species
forest inventory
forest pathology
forest species
forest stands classification
forest structure analysis
forestry
GEE
high-resolution remote sensing imagery
hyperspectral multitemporal information
illumination correction
imbalanced data
individual tree crown delineation
individual tree species recognition
ISRO-NASA campaign
Landsat
LiDAR
machine learning
machine learning algorithm
mapping
Mount Taishan
multi-layer perception
multi-temporal
multisource remote sensing data
multitemporal
myrtle rust
object-based
optical data
phenological metrics
pixel-based classification
probability random forest
radiative transfer model
random forest
RGB
SAR
savanna
scale effect
segmentation
selective logging
semideciduous forest
Sentinel-1
Sentinel-2
Serbia
Siberia
single trees
spatial autocorrelation
spatial divergence
species distribution model
species diversity
spectral diversity
time series
tree species
tree species classification
tree species mapping
trees species identification
tropical forests
UAV
up-scaling
urban forestry
Wienerwald biosphere reserve
woody vegetation
WorldView-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9911053076503321
MDPI - Multidisciplinary Digital Publishing Institute, 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui