Überwachte Methoden für die spektrale Entmischung mit künstlichen neuronalen Netzen
In this work, artificial neural networks trained in a supervised manner for spectral unmixing are investigated. For this purpose, a suitable network architecture is determined first. After that, the focus lies on the generation of suitable training data. Model-based methods that generate training da...
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Formatua: | Baliabide elektronikoa Liburu kapitulua |
Argitaratua: |
KIT Scientific Publishing
2023
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Saila: | Forschungsberichte aus der Industriellen Informationstechnik
29 |
Gaiak: | |
Sarrera elektronikoa: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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Gaia: | In this work, artificial neural networks trained in a supervised manner for spectral unmixing are investigated. For this purpose, a suitable network architecture is determined first. After that, the focus lies on the generation of suitable training data. Model-based methods that generate training data from real pure spectra and data-based methods that augment existing training data are presented and evaluated. |
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Deskribapen fisikoa: | 1 electronic resource (198 p.) |
ISBN: | KSP/1000159281 |
Sartu: | Open Access |