A transfer learning-based YOLO network for sewer defect detection in comparison to classic object detection methods

A transfer learning-based YOLO network for sewer defect detection in comparison to classic object detection methods

Deep learning has shown promising performance in automated sewer defect detection, however, is generally data-driven and computationally intensive. Transfer learning (TL) solves the problem of data limitations and avoids the need to build models from scratch. This study compared the performance of a...

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Bibliographic Details
Main Authors: Zuxiang Situ, Shuai Teng, Wanen Feng, Qisheng Zhong, Gongfa Chen, Jiongheng Su, Qianqian Zhou
Format: Article
Language:English
Published: Elsevier 2023-10-01
Series:Developments in the Built Environment
Subjects:
Object detection
Transfer learning
Pretrained CNNs
YOLO network
Sewer defects
Online Access:http://www.sciencedirect.com/science/article/pii/S266616592300073X

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http://www.sciencedirect.com/science/article/pii/S266616592300073X

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