文献
J-GLOBAL ID:202202226086981653
整理番号:22A1060213
時空間畳込みLSTMネットワークと同様の2次元畳込みニューラルネットワークによるアクティブサーモグラフィーにおける欠陥形状検出と欠陥再構成【JST・京大機械翻訳】
Defect shape detection and defect reconstruction in active thermography by means of two-dimensional convolutional neural network as well as spatiotemporal convolutional LSTM network
著者 (5件):
Mueller David
(Components & Assemblies, Fraunhofer Institute for Non-Destructive Testing IZFP, Saarbruecken, Germany)
,
Mueller David
(Research Group Quality Control and Maintenance,Faculty of Engineering, Saarland University of Applied Sciences, Saarbruecken, Germany)
,
Netzelmann Udo
(Components & Assemblies, Fraunhofer Institute for Non-Destructive Testing IZFP, Saarbruecken, Germany)
,
Valeske Bernd
(Components & Assemblies, Fraunhofer Institute for Non-Destructive Testing IZFP, Saarbruecken, Germany)
,
Valeske Bernd
(Research Group Quality Control and Maintenance,Faculty of Engineering, Saarland University of Applied Sciences, Saarbruecken, Germany)
資料名:
Quantitative InfraRed Thermography Journal
(Quantitative InfraRed Thermography Journal)
巻:
19
号:
2
ページ:
126-144
発行年:
2022年
JST資料番号:
W6037A
ISSN:
1768-6733
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
イギリス (GBR)
言語:
英語 (EN)