Improved recognition of E. coli 0157:H7 bacteria from pulsed-field gel electrophoresis images through the fusion of neural networks with fuzzy training data

E. coli 0157:H7 is a particularly toxic strain of the E. coli bacteria group. Fast and accurate methodologies for recognizing this strain of bacteria are desired. In this paper, we demonstrate that the fusion of neural network outputs using (possibly redundant) banding pattern features from pulsed-f...

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Hauptverfasser: Keller, J.M., Dayou Wang, Carson, C.A., McAdoo, K.K., Bailey, C.W.
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Dayou Wang
Carson, C.A.
McAdoo, K.K.
Bailey, C.W.
description E. coli 0157:H7 is a particularly toxic strain of the E. coli bacteria group. Fast and accurate methodologies for recognizing this strain of bacteria are desired. In this paper, we demonstrate that the fusion of neural network outputs using (possibly redundant) banding pattern features from pulsed-field electrophoresis images, where the learning was done with fuzzy labeled training data, produced superior results over the single and crisp counterparts.
doi_str_mv 10.1109/ICNN.1995.488858
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Biochemistry
Biological cells
Capacitive sensors
DNA
Electrokinetics
Image recognition
Microorganisms
Neural networks
Pathogens
Training data
title Improved recognition of E. coli 0157:H7 bacteria from pulsed-field gel electrophoresis images through the fusion of neural networks with fuzzy training data
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