Photoelastic Stress Field Recovery Using Deep Convolutional Neural Network

Recent work has shown that deep convolutional neural network is capable of solving inverse problems in computational imaging, and recovering the stress field of the loaded object from the photoelastic fringe pattern can also be regarded as an inverse problem solving process. However, the formation o...

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Detalles Bibliográficos
Autores principales: Tao, Bo, Wang, Yan, Qian, Xinbo, Tong, Xiliang, He, Fuqiang, Yao, Weiping, Chen, Bin, Chen, Baojia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Bioengineering and Biotechnology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8978563/
https://www.ncbi.nlm.nih.gov/pubmed/35387296
http://dx.doi.org/10.3389/fbioe.2022.818112

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8978563/
https://www.ncbi.nlm.nih.gov/pubmed/35387296
http://dx.doi.org/10.3389/fbioe.2022.818112

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