Comparative Analysis of Deep Learning Models for Structural Defect Segmentation in Bridges

• Published in: Proceedings of IEEE Southeastcon pp. 166 - 170
• Main Authors: O'Neal, Kiara, Hu, Da
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22.03.2025
• Subjects: Accuracy; Benchmark testing; Bridge infrastructure; Bridges; Corrosion; Deep learning; Defect detection; Feature extraction; Maintenance; Safety; Semantic segmentation

Automated structural defect detection is essential for ensuring the safety and maintenance of civil infrastructure, particularly in bridges where defects such as cracks, spalling, and corrosion can compromise structural integrity. This paper presents a comparative study of three semantic segmentatio...