As automation find its place in various industries, health monitoring is becoming more important than before. After all in an autonomous vehicle there is no driver to pay attention to strange noises or even realize that there is a flat tire.

Machine Learning in Industrial Diagnosis:

In this project we investigate the utility of machine learning in automotive health monitoring. More specifically we are interested in data efficient approaches to learning such as one/few shot learning. This approach is motivated by industry's lack of training data for diagnosis purposes.