Verification Of Perception Systems

A computer program product comprising computer executable instructions which, when executed by one or more processors, cause the one or more processors to carry out a method for verifying the robustness of a neural network classifier with respect to one or more parameterised transformations applied to an input, the classifier including one or more convolutional layers, the method including:

• encoding each layer of the classifier as one or more algebraic classifier constraints;
• encoding each transformation as one or more algebraic transformation constraints;
• encoding a change in an output classifier label from the classifier as an algebraic output constraint;
• determining whether a solution exists which satisfies the classifier constraints, transformation constraints and output constraints, and determining the classifier as robust to the local transformations if no such solution exists.

A perception system comprising one or more processors configured to carry out a method of for verifying the robustness of a neural network classifier with respect to one or more parameterised transformations applied to an input, the classifier including one or more convolutional layers, the method including:

• encoding each layer of the classifier as one or more algebraic classifier constraints;
• encoding each transformation as one or more algebraic transformation constraints;
• encoding a change in an output classifier label from the classifier as an algebraic output constraint;
• determining whether a solution exists which satisfies the classifier constraints, transformation constraints and output constraints, and determining the classifier as robust to the local transformations if no such solution exists.