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Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements



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Autore: Das Monidipa Visualizza persona
Titolo: Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements Visualizza cluster
Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica: 1 online resource (112 p.)
Soggetto topico: Environmental economics
Research and information: general
Soggetto non controllato: AOD recovery
CNN
conditional random fields
CYGNSS
Dirichlet process
East Asia
feature-level fusion
Gamma distribution
GNSS-R
high wind speed inversion
infinite mixture models
knowledge distillation
LightGBM
n/a
noisy labels
oil spill detection
online setting
optical image
PCA-SVR
polarized SAR
random forest
remote sensing images
scene classification
spatiotemporal weight interpolation
SVR
synthetic aperture radar images
teacher-student
variational inference
Persona (resp. second.): GhoshSoumya K
ChowdaryV. M
MitraPabitra
RijalSantosh
DasMonidipa
Sommario/riassunto: This book is a reprint of the Special Issue entitled "Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements" that was published in Remote Sensing, MDPI. It provides insights into both core technical challenges and some selected critical applications of satellite remote sensing image analytics.
Titolo autorizzato: Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910585940903321
Lo trovi qui: Univ. Federico II
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