Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …

Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …

With the extensive adoption of artificial intelligence (AI), construction engineering and
management (CEM) is experiencing a rapid digital transformation. Since AI-based solutions …

Non-destructive testing and characterization of internal vertical cracks are critical for road
maintenance by ground penetrating radar (GPR). This paper describes a mask region …

This paper describes a real-time, high-performance deep-learning network to segment
internal damages of concrete members at the pixel level using active thermography. Unlike …

Civil infrastructure (eg, buildings, roads, underground tunnels) could lose its expected
physical and functional conditions after years of operation. Timely and accurate inspection …

This paper presents an updated review of the external corrosion and failure mechanisms of
buried natural gas and oil pipelines. Various forms of external corrosion and failure …

Steel surfaces may exist some defects owing to imperfect manufacturing crafts and external
factors, which seriously influence the lifespan and availability of steel. Thus, surface defect …

Abstract Machine learning models have been shown to be useful for predicting and
assessing structural performance, identifying structural condition and informing preemptive …

Recently, crack segmentation studies have been investigated using deep convolutional
neural networks. However, significant deficiencies remain in the preparation of ground truth …