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Novel System for Rapid Investigation and Damage Detection in Cultural Heritage Conservation Based on Deep Learning
Publisher: American Society of Civil Engineers
Abstract: Rapid investigation and damage assessment are crucial for cultural heritage conservation. At present, mobile crowd sensing (MCS) techniques are very effective for cultural heritage investigation and data collection. ...
Leveraging Machine Learning for Pipeline Condition Assessment
Publisher: ASCE
Abstract: Pipeline condition assessment is a cost-effective method to determine the status of pipeline structure and predict failure probability. Although 100% inspection may not be feasible for decision makers, recent advancements ...
A Feature Selection–Based Intelligent Framework for Predicting Maximum Depth of Corroded Pipeline Defects
Publisher: ASCE
Abstract: Corrosion is one of the most common defects of buried pipelines. Accurate prediction of the maximum pitting depth of corroded pipelines is conducive to assessing the remaining strength of the pipeline. In the context of ...