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Deep learning-based research on the influence of training d..:

Chongyang Cui ; Shangchun Fan ; Han Lei..
https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9093. , 2019

Link: https://doi.org/10.1049/joe.2018.9093

RT Journal
T1 <Title>Deep learning-based research on the influence of training data size for breast cancer pathology detection</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:f23398afd564478f98beef1798fdbcb9&Exemplar=1&LAN=DE
				
A1 Chongyang Cui
A1 Shangchun Fan
A1 Han Lei
A1 Xiaolei Qu
A1 Dezhi Zheng
PB Wiley
YR 2019
K1 feature extraction
K1 learning (artificial intelligence)
K1 medical image processing
K1 patient diagnosis
K1 cancer
K1 neural nets
K1 image classification
K1 training data set
K1 training set
K1 pathology computer-assisted breast cancer analysis system
K1 different pathological images
K1 training data size
K1 breast cancer pathology detection
K1 pathological diagnosis
K1 deep learning-based computer-assisted pathology analysis systems
K1 Engineering (General). Civil engineering (General)
K1 TA1-2040
JF https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9093
LK http://dx.doi.org/https://doi.org/10.1049/joe.2018.9093
DO https://doi.org/10.1049/joe.2018.9093
SF ELIB - SuUB Bremen

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