Deep Learning-enhanced Hyperspectral Imaging for the Rapid Identification
and Classification of Foodborne Pathogens
Hanjing Ge
Abstract:Background:
Bacterial cellulose (BC) is a versatile biomaterial with numerous applications,
and the identification of bacterial strains that produce it is of great importance. This study explores
the effectiveness of a Stacked Autoencoder (SAE)-based deep learning method for the classification
of bacterial cellulose-producing bacteria.
Objective:
The primary objective of this research is to assess the potential of SAE-based classification
models in accurately identifying and classifying bacterial cellulose-p… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.