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机译:Comparison of classic object-detection techniques for automated sewer defect detection
Urban Development Research Center, Guangdong Urban & Rural Planning and Design Institute, No. 483 Nanzhou Road, Guangzhou 510290, China;
School of Civil and Transportation Engineering, Guangdong University of Technology, No. 100 Waihuan Xi Road, Guangzhou 510006, China;
Key words: deep learning; faster R-CNN; object detection; sewer defect detection; YOLO;