Abstract:In this contribution, we investigate a methodology based on neural networks for efficient learning of light metal castings for defect detection in X-ray imaging. The motivation comes from the high effort in time and costs which is currently required to set up new objects or parts. To overcome this drawback, on the one hand, we want to reduce the complexity for the user by applying neural networks for defect detection. On the other hand, we try to use as much data from the simulation as possible instead of real… Show more
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