Visual anomaly detection for automated quality control

Do you find visual quality control a costly and tedious but necessary task? Join our webinar to discover how neural networks can help you simplify and automate this task! What? How? Who? We will answer your questions to help you transform your quality control through visual inspection using artificial intelligence.

Neural networks, and especially convolutional networks, have drastically changed the possibilities of computer vision. On the other hand, visual quality control is an important part of industrial processes, but it remains a tedious and costly task.

Combining these two subjects allows for automated visual quality control, an important tool in our digital toolbox. 

This webinar addresses this challenge from three perspectives 

The first perspective is technical. It answers the question ‘What?’. What methods enable visual defect detection, how do they work, and what are their strengths and weaknesses?

The second perspective is more pragmatic. It answers the question ‘How?’. How can these technological building blocks be integrated into an industrial application? What process should be followed, from data collection to hardware selection and system monitoring?

For the last perspective, we need to zoom out to discuss the ‘Who?’. Again, an important choice must be made. Should everything be implemented in-house, or should a third party be relied upon? Should a solution be chosen that lies somewhere in between these two extremes?

In any case, we hope to provide you with knowledge so that you can engage with these topics actively and informed, whether you want to move forward internally or with a third party. 

Programme

This session is being organised as part of WalHub, the European Digital Innovation Hub (EDIH), bringing together experts dedicated to guiding Walloon manufacturing companies along the path of digital technologies in order to boost their competitiveness.  

©Agoria