Synthetic Data Pretraining for Hyperspectral Image Super-Resolution

Large-scale self-supervised pretraining of deep learning models is known to be critical in several fields, such as language processing, where its has led to significant breakthroughs. Indeed, it is often more impactful than architectural designs. However, the use of self-supervised pretraining lags...

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Główni autorzy:	Emanuele Aiello, Mirko Agarla, Diego Valsesia, Paolo Napoletano, Tiziano Bianchi, Enrico Magli, Raimondo Schettini
Format:	Artigo
Język:	Inglês
Wydane:	IEEE 2024-01-01
Seria:	IEEE Access
Hasła przedmiotowe:	Hyperspectral images super resolution synthetic data self-supervised pretraining spectral reconstruction
Dostęp online:	https://ieeexplore.ieee.org/document/10520906/
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