  We propose a novel technique to constrain parameters in CNN based on
symmetric filters. We investigate the impact on SOTA networks when varying the
combinations of symmetricity. We demonstrate that our models offer effective
generalisation and a structured elimination of redundancy in parameters. We
conclude by comparing our method with other pruning techniques.
