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A deep learning method for chamber enlargement diagnosis
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DC Field Value Language
dc.contributor.advisor 김대훈 -
dc.contributor.author Keonwoo Noh -
dc.date.accessioned 2022-07-07T02:29:23Z -
dc.date.available 2022-07-07T02:29:23Z -
dc.date.issued 2021 -
dc.identifier.uri http://dgist.dcollection.net/common/orgView/200000366283 en_US
dc.identifier.uri http://hdl.handle.net/20.500.11750/16727 -
dc.description.statementofresponsibility N -
dc.description.tableofcontents Abstract

1. Introduction
1.1 Computer vision with deep neural networks
1.2 Diagnosis chamber enlargement diseases with deep learning
1.3 Applying proper Data augmentation policies
2. Deep neural network models and data augmentation techniques
2.1 Deep neural network models
2.2 Automatic searching of data augmentation policies
3. Experiments
4. Conclusion
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dc.format.extent 13 -
dc.language eng -
dc.publisher DGIST -
dc.subject Deep learning, Computer vision, medical AI, Data augmentation, AutoML, 딥러닝, 컴퓨터 비전, 의료 인공지능 -
dc.title A deep learning method for chamber enlargement diagnosis -
dc.type Thesis -
dc.identifier.doi 10.22677/thesis.200000366283 -
dc.description.degree Master -
dc.contributor.department Information and Communication Engineering -
dc.identifier.bibliographicCitation Keonwoo Noh. (2021). A deep learning method for chamber enlargement diagnosis. doi: 10.22677/thesis.200000366283 -
dc.contributor.coadvisor Min-Soo Kim -
dc.date.awarded 2021/02 -
dc.publisher.location Daegu -
dc.description.database dCollection -
dc.citation XT.IM 노14 202102 -
dc.contributor.alternativeDepartment 정보통신융합전공 -
dc.embargo.liftdate 2024-02-29 -
dc.contributor.affiliatedAuthor Keonwoo Noh -
dc.contributor.affiliatedAuthor Daehoon Kim -
dc.contributor.affiliatedAuthor Min-Soo Kim -
dc.contributor.alternativeName 노건우 -
dc.contributor.alternativeName Daehoon Kim -
dc.contributor.alternativeName 김민수 -
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