Deep Learning in Manufacturing Processes

Deep Learning for Visual Anomaly Detection

The project aims to develop efficient and robust methods for recognising anomalies in objects in automated visual inspection. The main task of an inspection is the classification of objects into the class "O.K.", which means that the requirements for the object have been met, or into the class "n.O.K.", which means that an anomaly has been detected. Depending on the underlying task, the anomalies should also be localised.

As traditional image processing approaches quickly reach their limits, deep learning is used to solve the recognition problem. As the requirements in today's world are becoming increasingly complex and diverse, it is important that the methods developed adapt immediately to changes. Systems based on deep learning with neural networks offer efficient solutions to this challenge.