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Deep Learning Approach to Real-Time Health Monitoring for Fatigue Damage Detection and Classification
Deep Learning Approach to Real-Time Health Monitoring for Fatigue Damage Detection and Classification
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20220210163409
- ISBN
- 9798494497482
- DDC
- 658
- 서명/저자
- Deep Learning Approach to Real-Time Health Monitoring for Fatigue Damage Detection and Classification
- 발행사항
- [Sl] : The Pennsylvania State University, 2021
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2021
- 형태사항
- 158 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 83-06, Section: B.
- 주기사항
- Advisor: Ray, Asok;Marsh, Eric.
- 학위논문주기
- Thesis (Ph.D.)--The Pennsylvania State University, 2021.
- 일반주제명
- Industrial engineering
- 일반주제명
- Mechanics
- 일반주제명
- Artificial intelligence
- 일반주제명
- Mechanical engineering
- 키워드
- Fatigue damage
- 키워드
- Classification
- 키워드
- Detection
- 기본자료저록
- Dissertations Abstracts International. 83-06B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798494497482
■035 ▼a(MiAaPQ)AAI28929295
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a658
■1001 ▼aAlqahtani, Hassan.
■24510▼aDeep Learning Approach to Real-Time Health Monitoring for Fatigue Damage Detection and Classification
■260 ▼a[Sl]▼bThe Pennsylvania State University▼c2021
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2021
■300 ▼a158 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 83-06, Section: B.
■500 ▼aAdvisor: Ray, Asok;Marsh, Eric.
■5021 ▼aThesis (Ph.D.)--The Pennsylvania State University, 2021.
■590 ▼aSchool code: 0176.
■650 4▼aIndustrial engineering
■650 4▼aMechanics
■650 4▼aArtificial intelligence
■650 4▼aMechanical engineering
■653 ▼aAutomated monitoring
■653 ▼aFatigue damage
■653 ▼aClassification
■653 ▼aDetection
■653 ▼aFracture mechanics
■690 ▼a0346
■690 ▼a0800
■690 ▼a0548
■690 ▼a0546
■71020▼aThe Pennsylvania State University.
■7730 ▼tDissertations Abstracts International▼g83-06B.
■773 ▼tDissertation Abstract International
■790 ▼a0176
■791 ▼aPh.D.
■792 ▼a2021
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16056733▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202202▼f2022
