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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Bibliographic Details
Main Author: Anastasiadis, Johannes (auth)
Format: Electronic Book Chapter
Published: KIT Scientific Publishing 2023
Series:Forschungsberichte aus der Industriellen Informationstechnik
Subjects:
Online Access:DOAB: download the publication
DOAB: description of the publication
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245 1 0 |a Überwachte Methoden für die spektrale Entmischung mit künstlichen neuronalen Netzen 
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520 |a 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. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-sa/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-sa/4.0/ 
546 |a German 
650 7 |a Electrical engineering  |2 bicssc 
653 |a data generation; data augmentation; supervised training; artificial neural network; hyperspectral image; Datenerzeugung; Datenaugmentierung; überwachtes Training; Hyperspektralbild; künstliche neuronale Netze 
856 4 0 |a www.oapen.org  |u https://library.oapen.org/bitstream/20.500.12657/75890/1/uberwachte-methoden-fur-die-spektrale-entmischung-mit-kunstlichen-neuronalen-netzen.pdf  |7 0  |z DOAB: download the publication 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/121744  |7 0  |z DOAB: description of the publication