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| Autore: |
Das Monidipa
|
| Titolo: |
Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements
|
| 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 ![]() |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910585940903321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |