Funding for this research was provided by:
the Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN202000726)
the National Natural Science Foundation of China (62003063)
the Graduate Student Research Innovation Project of Chongqing (CYB240260)
the Science and Technology Research Program of Chongqing Municipal Education Commission of China (KJQN202200720)
Article Title: Lightweight concrete bridge damage detection by improved YOLOv5 and channel pruning algorithm
Journal Title: Measurement Science and Technology
Article Type: paper
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Publication dates
Date Received: 2024-10-09
Date Accepted: 2025-05-28
Online publication date: 2025-06-09