Cargando…
Determining the Spectral Requirements for Cyanobacteria Detection for the CyanoSat Hyperspectral Imager with Machine Learning
This study determines an optimal spectral configuration for the CyanoSat imager for the discrimination and retrieval of cyanobacterial pigments using a simulated dataset with machine learning (ML). A minimum viable spectral configuration with as few as three spectral bands enabled the determination...
Autores principales: | Matthews, Mark W., Kravitz, Jeremy, Pease, Joshua, Gensemer, Stephen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535531/ https://www.ncbi.nlm.nih.gov/pubmed/37765856 http://dx.doi.org/10.3390/s23187800 |
Ejemplares similares
-
CyanoClust: comparative genome resources of cyanobacteria and plastids
por: Sasaki, Naobumi V., et al.
Publicado: (2010) -
CyanoBase: the cyanobacteria genome database update 2010
por: Nakao, Mitsuteru, et al.
Publicado: (2010) -
CyanoOmicsDB: an integrated omics database for functional genomic analysis of cyanobacteria
por: Zhou, Peng, et al.
Publicado: (2021) -
Linear vs. Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Images
por: Cao, Faxian, et al.
Publicado: (2017) -
SpectralMAE: Spectral Masked Autoencoder for Hyperspectral Remote Sensing Image Reconstruction
por: Zhu, Lingxuan, et al.
Publicado: (2023)