TY - JOUR
T1 - Using Capsule Neural Network to predict Tuberculosis in lens-free microscopic images
AU - Núñez-Fernández, Dennis
AU - Ballan, Lamberto
AU - Jiménez-Avalos, Gabriel
AU - Coronel, Jorge
AU - Zimic, Mirko
N1 - Publisher Copyright:
Copyright © 2020, The Authors. All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/7/5
Y1 - 2020/7/5
N2 - Tuberculosis, caused by a bacteria called Mycobacterium tuberculosis, is one of the most serious public health problems worldwide. This work seeks to facilitate and automate the prediction of tuberculosis by the MODS method and using lens-free microscopy, which is easy to use by untrained personnel. We employ the CapsNet architecture in our collected dataset and show that it has a better accuracy than traditional CNN architectures.
AB - Tuberculosis, caused by a bacteria called Mycobacterium tuberculosis, is one of the most serious public health problems worldwide. This work seeks to facilitate and automate the prediction of tuberculosis by the MODS method and using lens-free microscopy, which is easy to use by untrained personnel. We employ the CapsNet architecture in our collected dataset and show that it has a better accuracy than traditional CNN architectures.
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M3 - Article
AN - SCOPUS:85095265982
JO - Advances in Water Resources
JF - Advances in Water Resources
SN - 0309-1708
ER -