L1 Regularization based Learning Method for Capsule Network

Abstract

Capsule Network is a new neural network proposed to overcome the shortcomings of CNN. However, the Capsule Network has many learnable parameters and is prone to over- tting. In this research, we aim to improve general- ization ability by reducing parameters using L1 regularization. We evaluate our method by comparing the accuracy and the reconstructed image with the conventional method.