Patent ID: 11947625
Assignee: ROBERT BOSCH GMBH
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 14:
15. A computer configured to train a neural network that maps input images onto an association with one or multiple classes of a predefined classification, onto a semantic segmentation, and/or onto a recognition of one or multiple objects, as output data, the computer configured to:
provide learning input images and associated learning output data onto which the neural network ideally is to map the learning input images;
provide auxiliary input images;
generate modifications of the auxiliary input images by introducing at least one predefined change into each auxiliary input image of the auxiliary input images;
supply the modifications to the neural network;
ascertain predictions for the predefined change, using output data onto which the neural network maps each of the modifications;
assess deviations of the predictions from the predefined change, using a predefined auxiliary cost function;
optimize parameters that characterize a behavior of the neural network, with an objective of improving the assessment by the auxiliary cost function during further processing of the auxiliary input images;
supply the learning input images to the neural network;
assess deviations of output data, onto which the neural network maps the supplied learning input images, from the learning output data, using a main cost function;
optimize parameters which characterize the behavior of the neural network with an objective of improving the assessment by the main cost function during further processing of the learning input images.