ADVANCED DEEP LEARNING IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING
Ph.D
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2021
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Online Access: | https://scholarbank.nus.edu.sg/handle/10635/191723 |
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sg-nus-scholar.10635-1917232024-10-25T12:05:40Z ADVANCED DEEP LEARNING IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING GUO YILIN MECHANICAL ENGINEERING Ying Hsi,Jerry Fuh Lu Wen-Feng design for additive manufacturing, cellular structure, multiscale topology optimization, deep learning, anomaly detection, predictive uncertainty Ph.D DOCTOR OF PHILOSOPHY (FOE) 2021-05-31T18:00:54Z 2021-05-31T18:00:54Z 2021-01-05 Thesis GUO YILIN (2021-01-05). ADVANCED DEEP LEARNING IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING. ScholarBank@NUS Repository. https://scholarbank.nus.edu.sg/handle/10635/191723 0000-0003-4237-2112 en |
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National University of Singapore |
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NUS Library |
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Asia |
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Singapore Singapore |
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NUS Library |
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ScholarBank@NUS |
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English |
topic |
design for additive manufacturing, cellular structure, multiscale topology optimization, deep learning, anomaly detection, predictive uncertainty |
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design for additive manufacturing, cellular structure, multiscale topology optimization, deep learning, anomaly detection, predictive uncertainty GUO YILIN ADVANCED DEEP LEARNING IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING |
description |
Ph.D |
author2 |
MECHANICAL ENGINEERING |
author_facet |
MECHANICAL ENGINEERING GUO YILIN |
format |
Theses and Dissertations |
author |
GUO YILIN |
author_sort |
GUO YILIN |
title |
ADVANCED DEEP LEARNING IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING |
title_short |
ADVANCED DEEP LEARNING IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING |
title_full |
ADVANCED DEEP LEARNING IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING |
title_fullStr |
ADVANCED DEEP LEARNING IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING |
title_full_unstemmed |
ADVANCED DEEP LEARNING IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING |
title_sort |
advanced deep learning in optimal design for additive manufacturing |
publishDate |
2021 |
url |
https://scholarbank.nus.edu.sg/handle/10635/191723 |
_version_ |
1821206083080814592 |