Full metadata record
| 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 |
- |
| 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.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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