Semi-supervised anomaly detection from Chlorella vulgaris cultivations using hyperspectral imaging
Description
These data include hyperspectral images of microalgae cultivations, files for data preprocessing, principal component analysis (PCA), and semi-supervised anomaly detection models.
Show moreYear of publication
2025
Authors
University of Jyväskylä - Publisher
Other information
Fields of science
Computer and information sciences; Plant biology, microbiology, virology; Other engineering and technologies
Language
English
Open access
Open