Automatic sewer defect detection and severity quantification based on pixel-level semantic segmentation

•Automated pixel-level sewer defects detection and segmentation.•DeepLabv3+ with five types of backbones are compared with FCN, U-Net and SegNet.•Severity quantification by means of geometric assessment of sewer defects.•Multiple types of sewer defects under complex conditions.•DeepLabv3+-Resnet50 a...

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Veröffentlicht in:	Tunnelling and underground space technology 2022-05, Vol.123, p.104403, Article 104403
Hauptverfasser:	Zhou, Qianqian, Situ, Zuxiang, Teng, Shuai, Liu, Hanlin, Chen, Weifeng, Chen, Gongfa
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer networks Decision making DeepLabv3 Defects Inspection Pixel level Pixels Repair & maintenance Semantic segmentation Sensors Severity quantification Sewer defect detection Sewer maintenance Sewer systems
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