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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 electronic resource (112 p.)
Soggetto topico: Research & information: general
Environmental economics
Soggetto non controllato: scene classification
teacher-student
noisy labels
knowledge distillation
remote sensing images
LightGBM
spatiotemporal weight interpolation
AOD recovery
East Asia
polarized SAR
optical image
random forest
conditional random fields
feature-level fusion
Dirichlet process
infinite mixture models
Gamma distribution
variational inference
online setting
oil spill detection
synthetic aperture radar images
GNSS-R
CYGNSS
high wind speed inversion
SVR
PCA-SVR
CNN
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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