SOURCE-LINKED INTELLIGENCE

Machine Learning for Structural Health Monitoring of Cultural Heritage

CORDIS · observation · Publication date unknown

Machine Learning for Structural Health Monitoring of Cultural Heritage Europe is home to about 400 UNESCO world heritage sites and has a growing tourism industry employing many people directly and indirectly. Hence, it is of concern to ensure the cultural heritage (CH) buildings are inspected properly and correct damage diagnosis is performed. Incorrect damage diagnosis will lead to loss of cultural value and may lead to the closing of the monument, thus affecting society in general and the livelihood of people associated with it. The proposed MLCULT project is motivated by the need to perform damage diagnosis of CH using image-based machine learning (ML) techniques, thus helping to preserve them. The popularity of ML approaches and deep learning algorithms has increased considerably over the last two decades. Computer-vision-based damage detection employing convolutional neural networks

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recordType

award

status

SIGNED

region

EU

value

172618.56

unit

EUR