SENSOR SYSTEM INCLUDING ARTIFICIAL NEURAL NETWORK CONFIGURED TO PERFORM A CONFIDENCE MEASURE-BASED CLASSIFICATION OR REGRESSION TASK

摘要

A sensor system includes at least one sensor and an evaluation device that is configured for receiving input data x from the at least one sensor, and that comprises at least one trained artificial neural network that is configured to perform a classification or regression task on input data x, wherein the at least one trained artificial neural network comprises an M_Θ-module as an implementation of a machine learning based method for the classification or regression task with trainable parameters Θ. The sensor system further comprises a confidence measure module arrangement that includes a D_p- module as implementation of a machine learning based method that is configured to learn a representation of the training dataset with trainable parameters, and an E-module as implementation of a measure to determine how far the input data x are from the training dataset using the information of DΦ. The confidence measure module arrangement is configured to utilize said output being combined with the output of M_Θ to decide whether the module is allowed to perform an action (classification or regression task based on the input data x).