Autonomous Structural Visual Inspection Using Region‐Based Deep Learning for Detecting Multiple Damage Types

Computer vision‐based techniques were developed to overcome the limitations of visual inspection by trained human resources and to detect structural damage in images remotely, but most methods detect only specific types of damage, such as concrete or steel cracks. To provide quasi real‐time simultan...

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Veröffentlicht in:	Computer-aided civil and infrastructure engineering 2018-09, Vol.33 (9), p.731-747
Hauptverfasser:	Cha, Young‐Jin, Choi, Wooram, Suh, Gahyun, Mahmoudkhani, Sadegh, Büyüköztürk, Oral
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Computer vision Corrosion Damage detection Deep learning Flaw detection Fracture mechanics Human resources Image detection Pixels Structural damage Structural steels
Online-Zugang:	Volltext
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