Semi-supervised anomaly detection from Chlorella vulgaris cultivations using hyperspectral imaging
More evolved anomaly detection methods are needed to ensure efficient quality control of microalgae cultivations. This study aimed to determine whether non-invasively collected hyperspectral data can be used to indicate anomalies in Chlorella vulgaris cultivations. Three models of varying computatio...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
|
| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375525003545 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|