Deep Learning for Visual Inspection & Defect Detection
In some production applications, defects or deviations can vary significantly and may be difficult to describe using fixed inspection rules.
Machine vision systems with deep learning are trained using example images to recognize patterns, characteristics and deviations. This makes them suitable for complex visual inspection applications where conventional rule-based machine vision methods may not always be sufficient.
Deep learning applications in production
Defect Detection
Detection of complex or variable defects that may be difficult to describe using predefined inspection rules.
Product Classification
Classification of products or components according to visual characteristics used during system training.
Object Detection
Detection of specific objects or features within an image for inspection and automation applications.
Visual Feature Inspection
Evaluation of characteristics such as appearance, texture or other visual deviations depending on the requirements of the application.
Production line integration
The appropriate deep learning solution depends on the product, the type of defects or characteristics to be identified, sample variability and application conditions.
At Robovision, we analyze the application, collect and evaluate suitable image samples, and integrate the machine vision solution into the production process.
