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Huang, Tianrui, Gao, Yang, Li, Zhenglin, Hu, Yue, Xuan, Fuzhen (2023) A Hybrid Deep Learning Framework Based on Diffusion Model and Deep Residual Neural Network for Defect Detection in Composite Plates. Applied Sciences, 13 (10) 5843 doi:10.3390/app13105843

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Reference TypeJournal (article/letter/editorial)
TitleA Hybrid Deep Learning Framework Based on Diffusion Model and Deep Residual Neural Network for Defect Detection in Composite Plates
JournalApplied Sciences
AuthorsHuang, TianruiAuthor
Gao, YangAuthor
Li, ZhenglinAuthor
Hu, YueAuthor
Xuan, FuzhenAuthor
Year2023 (May 9)Volume13
Issue10
PublisherMDPI AG
DOIdoi:10.3390/app13105843Search in ResearchGate
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Mindat Ref. ID15843913Long-form Identifiermindat:1:5:15843913:8
GUID0
Full ReferenceHuang, Tianrui, Gao, Yang, Li, Zhenglin, Hu, Yue, Xuan, Fuzhen (2023) A Hybrid Deep Learning Framework Based on Diffusion Model and Deep Residual Neural Network for Defect Detection in Composite Plates. Applied Sciences, 13 (10) 5843 doi:10.3390/app13105843
Plain TextHuang, Tianrui, Gao, Yang, Li, Zhenglin, Hu, Yue, Xuan, Fuzhen (2023) A Hybrid Deep Learning Framework Based on Diffusion Model and Deep Residual Neural Network for Defect Detection in Composite Plates. Applied Sciences, 13 (10) 5843 doi:10.3390/app13105843
In(2023, May) Applied Sciences Vol. 13 (10) MDPI AG

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