Deep learning has undoubtedly opened up many areas of industry that had been previously inaccessible for traditional machine vision. There is no longer a need to spend weeks on creating rule-based algorithms for quality inspection and eventually end up having to completely re-design them due to slight changes in the object shape or structure. Not to mention tasks that were simply not feasible in the past, whereas now, using tools for feature and anomaly detection, we can approach them and move ahead of our competitors.  

It turns out, however, that deep learning-based tools more and more often end up complementing traditional machine vision and the best results are achieved when we put them together. 

In this webinar, you will learn how to combine deep learning with traditional machine vision algorithms using real-life projects as an example.