Training data

We use artificial neural networks (ANN) for the automated analysis of geometric measurement data; ANNs are individually trained for specific applications using our own training data. To ensure the best possible analysis results, we rely on manual annotations. We use our proprietary tools for the automated annotation of point clouds to make our training data generation as efficient as possible. We’re also investigating the use of synthetic training data to make ANN training even more efficient.