Abstract: A device and method for evaluating a control of a generator for determining pixels of a synthetic image. The generator determining pixels of the synthetic image from a first input comprising a label map and a first latent code. The method includes providing the label map and latent code which includes input data points in a latent space; providing the control including a set of directions for moving the latent code in the latent space, determining the first latent code depending on at least one input data point of the latent code that is moved in a first direction which is selected from the set of directions, determining a distance between at least one pair of synthetic images generated by the generator for different first inputs which comprise the label map and vary by the first direction that is selected for determining the first latent code from the latent code.

Abstract: A device and computer-implemented method for determining pixels of a synthetic image. The method comprises providing a generator that is configured to determine an output from a first input comprising a label map and a first latent code, wherein the label map comprises a mapping of at least one class to at least one of the pixels, wherein the method comprises providing the label map and a latent code, wherein the latent code comprises input data points in a latent space, providing a first direction for moving input data points in the latent space, determining the first latent code depending on at least one input data point of the latent code that is moved in the first direction, determining the synthetic image depending on an output of the generator for the first input.

Abstract: A computer-implemented method for training an artificial intelligence module to determine a tire type of a motor vehicle is disclosed. The method includes providing a measured value dataset on a data carrier, wherein the measured value dataset contains at least one data entry regarding ultrasound data, speed data and tire data, wherein the ultrasound data describe at least one ultrasonic wave that was produced by rolling of a tire of the motor vehicle, wherein the speed data describe a speed of the motor vehicle, wherein the tire data describe a tire type of the motor vehicle. The method further includes generating a modified training dataset based on the measured value dataset. Generating the modified training dataset includes (i) forming an input dataset based on the ultrasound data and the speed data of the measured value dataset, (ii) forming an output dataset based on the tire data of the measured value dataset, and (iii) training the AI module based on the modified training dataset.

Abstract: A computer-implemented method for generating training data for machine learning and a machine learning method, in particular a self-monitored learning method. The learning method using training data which are generated according to a method for training a neural network.