A computer-implemented method of optimising a student neural network (SNN), based on a previously-trained neural network (PTNN) trained on first data (FD) using a first processing system (FPS). The method includes using a second processing system (SPS) to generate reference output data (ROD) from the previously-trained neural network (PTNN) in response to inputting second data (SD) to the previously-trained neural network (PTNN). The method also includes optimising a student neural network (SNN) for processing the second data (SD) with the second processing system (SPS), by using the second processing system (SPS) to adjust a plurality of parameters of the student neural network (SNN) such that a difference (DIFF) between the reference output data (ROD), and second output data (SOD) generated by the student neural network (SNN) in response to inputting the second data (SD) to the student neural network (SNN), satisfies a stopping criterion.