Incorporating Inductive Bias into Deep Learning: A Perspective from Automated Visual Inspection in Aircraft Maintenance

Application of LSTM network for Structural Health Monitoring & Non-Destructive Testing

Perception Modelling by Invariant Representation of Deep Learning for Automated Structural Diagnostic in Aircraft Maintenance: A Study Case using DeepSHM

This project presents the possibility of utilizing Convolutional Neural Networks in image processing to analyze structures and the possible damages that have occured to them

Learning based Image Scale Estimation (LISE) for Quantitative Visual Inspection

Structural Health Monitoring is one of the recent area which has not seen significant application of deep-neural network. The major limitation is due to unavailability of huge number of labeled data set.

Open-source framework for infrastructure defect detection with transfer learning. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001503

Repository containing multiple EOV Mitigation Procedures for Structural Health Monitoring.

Frequency Domain Decomposition, including Peak Picking technique

This repository contains Python scripts used to obtain results from the paper "A Latent Variable Approach for Mitigation of Environmental and Operational Variability in Vibration-Based SHM – A Linear Approach," presented at the EWSHM2024.

Defect Detection and Quantification Toolbox