Classification Methods for Remotely Sensed Data
The new edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data, and presents new AI-based analysis tools and metrics together with ongoing debates on accuracy asse...
| Otros Autores: | , , |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
CRC Press
[2025]
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| Edición: | Third edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009869097406719 |
| Sumario: | The new edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data, and presents new AI-based analysis tools and metrics together with ongoing debates on accuracy assessment strategies and XAI methods. |
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| Notas: | Revised edition of: Classification methods for remotely sensed data / Brandt Tso, Paul M. Mather. 2nd ed. 2009. |
| Descripción Física: | 1 online resource (444 pages) |
| ISBN: | 9781040099056 9781040099117 9781003439172 |
