Computer-implemented method for monitoring a deep neural network and applications thereof

A computer-implemented method for monitoring an artificial deep neural network, which has a multiplicity of network layers, each having at least one artificial neuron, wherein the method comprises:

• a) supplying input data to a deep neural network to be monitored, which is trained for a task, in order to obtain therefrom output data and activation map data, wherein the output data are generated in accordance with the trained task, wherein the activation map data indicate for each neuron what activation value this neuron has;
• b) supplying the input data, the output data and the activation map data to a computer-implemented network observer which carries out the following steps of:
• aa) generating masking data from the activation map data and/or the input data and/or the output data;
• bb) masking the activation map data using the masking data in order to obtain masked activation map data, wherein the masked activation map data contain unmasked activation values and masked activation values;
• cc) determining an outlier score for the output data using the masked activation map data, wherein merely the unmasked values are taken into account when determining the outlier score, wherein the outlier score is a numerical value;
• dd) assigning the outlier score to the respective output data and, optionally, to the input data for further joint processing.