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A Lightweight Parallel Attention U-Net for Surface Defect Segmentation of Wind Turbine Towers in Visible-Light Images.

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Title: A Lightweight Parallel Attention U-Net for Surface Defect Segmentation of Wind Turbine Towers in Visible-Light Images.
Authors: Zeng, Fanqiang1, Wu, Renchaogetu2, Ma, Yinan1, Zhang, Yu1,2, Ping, Wanpeng1, Yang, Songbin1, Gao, Qingfei2, gaoqingfei@hit.edu.cn
Source: Buildings (2075-5309); Jul2026, Vol. 16 Issue 14, p2837, 31p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 195804957
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PubType: Academic Journal
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  Data: A Lightweight Parallel Attention U-Net for Surface Defect Segmentation of Wind Turbine Towers in Visible-Light Images.
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      – Type: doi
        Value: 10.3390/buildings16142837
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        Text: English
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      – TitleFull: A Lightweight Parallel Attention U-Net for Surface Defect Segmentation of Wind Turbine Towers in Visible-Light Images.
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              Text: Jul2026
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              Y: 2026
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