Performance Comparison of Deep Learning Models for Damage Identification of Aging Bridges

Performance Comparison of Deep Learning Models for Damage Identification of Aging Bridges

Currently, damage in aging bridges is assessed visually, leading to significant personnel, time, and cost expenditures. Moreover, the results depend on the subjective judgment of the inspector. Machine-learning-based approaches, such as deep learning, can solve these problems. In particular, instanc...

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Bibliographic Details
Main Authors: Su-Wan Chung, Sung-Sam Hong, Byung-Kon Kim
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Applied Sciences
Subjects:
deep learning
aging-bridge management
instance segmentation
damage identification
loss–functions
Online Access:https://www.mdpi.com/2076-3417/13/24/13204

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