Marcos Spínola Neto

An Adaptive Unsupervised Structural Health Monitoring Framework Using Exclusion-Aware Convolutional Autoencoders

Abstract Structural health monitoring (SHM) plays an important role in ensuring the safety and durability of civil structures. Among various SHM methodologies, autoencoders have proven particularly effective for anomaly detection due to their ability to extract meaningful feature...