Synthetic data gives us the possibility to steer AI vision algorithms
Imagine spending countless hours taking pictures and annotating said pictures, only to find out that the dataset that was created does not match reality closely enough to be of any worth…. With the usage of synthetic data this process can be drastically streamlined, improved and optimized. Synthetic data, as the name already implies, is artificial data created by a computer.
This creation of data opens a world of opportunities. Once the desired synthetic environment is set up it allows not only for infinite customization, i.e. different environment (lighting) conditions, specific (physics) constraints, but also fast, cheap and accurate pixel-level labeled data creation. By making use of synthetic data it is possible to model and represent many edge cases in the dataset, in order to create a robust input for Machine Learning.
This combination allows for full control over the desired data and the ability to rapidly prototype and iterate AI algorithms. This iteration step is of crucial importance since this is necessary to ensure the robustness of the algorithms. In this step the AI algorithm can be steered and optimized using specifically directed synthetic data.
At Newcircle Technologies we have expertise and experience in the field of synthetic data. In the video above, the synthetic environment can be seen. The input for this environment is a 3D drawing or scan of a (series of) product(s). The data obtained from this environment is subsequently used to train an AI detection network.
