Stage - AI inspection for inkjet printing with rapidly changing designs

AI-Powered Inkjet Print Inspection for Rapidly Changing Designs In this internship, you will investigate how AI can make the inspection process more generic and reduce the engineering effort for new products. Goal Develop a flexible AI‑driven print inspection approach that can start with limited or no labeled data and then quickly adapt to new prints and defect types. What are you going to do? Investigate how visual print inspection can be built with limited labeled data in combination with synthetic data Apply techniques such as data augmentation, transfer learning, and domain adaptation to photos of previous products and prints to quickly develop an inspection model for a new print Compare the different supervised AI methods with an anomaly detection approach Explore continuous and incremental learning strategies (such as few‑shot and online learning) to enable pre‑existing models to grow with new products and defect types Required Skills Experience with Python Interest in computer vision and machine learning Affinity with industrial applications or quality inspection Prior experience with synthetic data or data augmentation techniques #J-18808-Ljbffr Innovation Cluster Drachten