| contributor author | Liao, Yanna | |
| contributor author | Tong, Xinyu | |
| contributor author | Yin, Yafang | |
| date accessioned | 2026-08-20T12:00:24Z | |
| date available | 2026-08-20T12:00:24Z | |
| date copyright | 2026/05/16 | |
| date issued | 2026 | |
| identifier other | JPCFEV.CFENG-5387.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4312963 | |
| description abstract | AbstractThis study proposes mix transformer-enhanced UNet (MiTE-UNet), an improved UNet architecture
based on a hybrid convolutional neural network (CNN)–transformer framework, for concrete
building surface defect segmentation. The proposed model is ...Practical ApplicationsConcrete buildings such as bridges and tunnels often develop surface defects over
time, and, if not detected early, these issues may worsen and pose safety risks. Traditional
manual inspections are slow and labor-intensive and often ... | |
| publisher | American Society of Civil Engineers | |
| title | A Mix Transformer–Enhanced UNet for Concrete Building Surface Defect Semantic Segmentation | |
| type | Journal Article | |
| journal volume | 40 | |
| journal issue | 4 | |
| journal title | Journal of Performance of Constructed Facilities | |
| identifier doi | 10.1061/JPCFEV.CFENG-5387 | |
| journal fristpage | 04026019-1 | |
| journal lastpage | 04026019-14 | |
| page | 14 | |
| tree | Journal of Performance of Constructed Facilities:;2026:;Volume ( 040 ):;issue: 004 | |
| contenttype | Fulltext | |