End-to-End Convolutional Autoencoder for Nonlinear Hyperspectral Unmixing

Hyperspectral Unmixing is the process of decomposing a mixed pixel into its pure materials (endmembers) and estimating their corresponding proportions (abundances). Although linear unmixing models are more common due to their simplicity and flexibility, they suffer from many limitations in real worl...

Whakaahuatanga katoa

I tiakina i:

Ngā taipitopito rārangi puna kōrero
Ngā kaituhi matua:	Mohamad Dhaini, Maxime Berar, Paul Honeine, Antonin Van Exem
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	MDPI AG 2022-07-01
Rangatū:	Remote Sensing
Ngā marau:	convolutional neural network autoencoder hyperspectral imaging nonlinear spectral unmixing
Urunga tuihono:	https://www.mdpi.com/2072-4292/14/14/3341
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

End-to-End Convolutional Autoencoder for Nonlinear Hyperspectral Unmixing

Ngā tūemi rite