In this thesis capsule networks are investigated, both theoretically and empirically. The properties of the dynamic routing [42] algorithm proposed for capsule networks, as well as a routing algorithm in a follow-up paper by Wang et al. [50] are thoroughly investigated. It is conjectured that there are three key attributes that are needed for a good routing algorithm, and these attributes are then related to previous algorithms. A novel routing algorithm EntMin is proposed based on the observations from the investigation of previous algorithms. A thorough evaluation of the performance of different aspects of capsule networks is conducted, and it is shown that EntMin outperforms both dynamic routing and Wang routing. Finally, a capsule network using EntMin routing is compared to a very deep Convolutional Neural Network and it is shown that it achieves comparable performance.