Anomaly Detection

 by Giulio Galvan

Deep learning for quality controls of mechanical components

One of the many aspects where deep learning is revolutionizing the industry is that of quality control and fault detection.

 

This blog post describes the result of a collaboration between flair-tech and Qvision for the quality control of mechanical components. The problem is to check whether a spherical mechanical part, is correctly glued to a surface.

 

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in Anomaly Detection / Data Science / Deep Learning / Machine Learning 0 comments
 by Giulio Galvan

Why anomaly detection is not binary classification

 

Anomaly detection refers to the problem of finding patterns in data that do not
conform to expected behavior.

—Chandola et al., Anomaly Detection: A Survey

Like a fish swimming upstream, the mouse befriending the cat and the rich giving to the poor.

But also like

  • the malicious user in your organization
  • the defecting engine you just manufactured
  • the fraudulent credit card transaction you just processed
  • the unreasonable network traffic on your servers
  • …

It seems that Anomaly Detection amounts to all but separate the good from the bad. And in fact, it is. So why not dig up the good old binary classification?

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