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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
Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019
Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019
Autore Matese Alessandro
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 online resource (184 p.)
Soggetto topico Biology, life sciences
Forestry & related industries
Research & information: general
Soggetto non controllato Accuracy Assessment
ancient trees measurement
biomass evaluation
burn severity
Castanea sativa
central Oregon
classification
convolutional neural network
convolutional neural network (CNN)
ecohydrology
end-to-end learning
establishment survey
forest fire
forest inventory
forest modeling
forest regeneration
Forest Sampling
forestry applications
hyperspectral imagery
image processing
juniper woodlands
leaf-off
leaf-on
machine learning
Mauritia flexuosa
multispectral classification
multispectral image
object-based image analysis (OBIA)
photogrammetric point clouds
Photogrammetry
precision agriculture
precision forestry
rangelands
Reference Data
reforestation
remote sensing
Remote Sensing
reproduction
RGB imagery
Robinia pseudoacacia L.
seedling detection
seedling stand inventorying
semantic segmentation
short rotation coppice
spreading
structure from motion (SfM)
Thematic Mapping
tree age prediction
UAV
UAV photogrammetry
unmanned aerial system (UAS)
unmanned aerial systems
Unmanned Aerial Systems (UAS)
unmanned aerial vehicles
unmanned aerial vehicles (UAV)
Unmanned Aerial Vehicles (UAV)
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Forestry Applications of Unmanned Aerial Vehicles
Record Nr. UNINA-9910557112103321
Matese Alessandro  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui