Semantic Segmentation in Satellite Hyperspectral Imagery by Deep Learning

Satellites are increasingly adopting on-board AI to optimize operations and increase autonomy through in-orbit inference. The use of Deep Learning (DL) models for segmentation in hyperspectral imagery offers advantages for remote sensing applications. In this work, we train and test 20 models for mu...

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Veröffentlicht in:	arXiv.org 2024-10
Hauptverfasser:	Jon Alvarez Justo, Ghita, Alexandru, Kovac, Daniel, Garrett, Joseph L, Georgescu, Mariana-Iuliana, Gonzalez-Llorente, Jesus, Radu Tudor Ionescu, Johansen, Tor Arne
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Data processing Deep learning Hyperspectral imaging Image classification Image segmentation Inference Machine learning Mathematical models One dimensional models Parameters Remote sensing Satellite imagery Satellites Spectral signatures
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