다중 해상도를 이용한 딥러닝 기반 창상 분류 방법
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박경리 | - |
dc.contributor.author | 김지훈 | - |
dc.contributor.author | 김해문 | - |
dc.contributor.author | 차지환 | - |
dc.contributor.author | 유희진 | - |
dc.contributor.author | 문영식 | - |
dc.date.accessioned | 2023-09-04T05:44:06Z | - |
dc.date.available | 2023-09-04T05:44:06Z | - |
dc.date.issued | 2021-11 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/114959 | - |
dc.description.abstract | In medical data, the distance between the wound and the imaging device is not constant, so there is a problem that the deep learning model becomes sensitive to changes in resolution. To solve this problem, in this paper, we propose a network that is robust to resolution changes through multiple resolution input. Experimentally, the proposed method is more robust to resolution changes than the existing method, and shows 1.48% higher performance. | - |
dc.format.extent | 5 | - |
dc.language | 한국어 | - |
dc.language.iso | KOR | - |
dc.publisher | 대한전자공학회 | - |
dc.title | 다중 해상도를 이용한 딥러닝 기반 창상 분류 방법 | - |
dc.title.alternative | Deep Learning Based Wound Classification Method Using Multiple Resolutions | - |
dc.type | Article | - |
dc.publisher.location | 대한민국 | - |
dc.identifier.bibliographicCitation | 2021년 대한전자공학회 추계학술대회 논문집, pp 482 - 486 | - |
dc.citation.title | 2021년 대한전자공학회 추계학술대회 논문집 | - |
dc.citation.startPage | 482 | - |
dc.citation.endPage | 486 | - |
dc.type.docType | Proceeding | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | other | - |
dc.identifier.url | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11027634 | - |
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