Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Pujin Wang"'
Publikováno v:
Ceramics International. 49:20210-20217
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2067715a9fd2f96cd7dd7a174f95b111
https://doi.org/10.1016/j.ceramint.2023.03.145
https://doi.org/10.1016/j.ceramint.2023.03.145
Publikováno v:
ACS Sustainable Chemistry & Engineering. 11:6652-6664
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5fd9d57213542828128b6dd1ae9951ae
https://doi.org/10.1021/acssuschemeng.3c00003
https://doi.org/10.1021/acssuschemeng.3c00003
Publikováno v:
Materials Research Bulletin. 162:112190
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc0b0fc3c6a23eb2971ec60383371704
https://doi.org/10.1016/j.materresbull.2023.112190
https://doi.org/10.1016/j.materresbull.2023.112190
Publikováno v:
Journal of Cleaner Production. 400:136538
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f10346795c864d7a34957acbfe33ab6
https://doi.org/10.1016/j.jclepro.2023.136538
https://doi.org/10.1016/j.jclepro.2023.136538
Publikováno v:
Sustainability; Volume 14; Issue 6; Pages: 3275
To alleviate the workload in prevailing expert-based onsite inspection, a vision-based method using state-of-the-art deep learning architectures is proposed to automatically detect ceiling damage in large-span structures. The dataset consists of 914
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3ad6c794cbf248ad2815ea8833fc8a1
https://doi.org/10.3390/su14063275
https://doi.org/10.3390/su14063275
Publikováno v:
Automation in Construction. 116:103230
To overcome the limitations of human-based visual onsite inspections, a vision-based method using deep learning with a convolutional neural network (CNN) is proposed to detect and localize the damaged ceiling of large-span structures. The designed CN
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::082381858d56fd8e06d901012500b74e
https://doi.org/10.1016/j.autcon.2020.103230
https://doi.org/10.1016/j.autcon.2020.103230