论文标题
胶囊网络最新进展的有效性
Effectiveness of the Recent Advances in Capsule Networks
论文作者
论文摘要
卷积神经网络（CNN）彻底改变了深度神经网络的领域。然而，最近的研究表明，CNN在各种条件下未能概括，因此胶囊的想法是在2011年引入的，尽管真正的研究的真正激增始于2017年。在本文中，我们概述了胶囊结构和路由机制的最新进展。此外，我们发现最近文献中的相对重点是修改路由程序或整个体系结构，但对其他更细的组件的研究，特别是壁球功能所需的。因此，我们还提供了一些有关南瓜功能在胶囊网络性能中的影响的新见解。最后，我们通过讨论和提出胶囊网络领域可能的机会来得出结论。
Convolutional neural networks (CNNs) have revolutionized the field of deep neural networks. However, recent research has shown that CNNs fail to generalize under various conditions and hence the idea of capsules was introduced in 2011, though the real surge of research started from 2017. In this paper, we present an overview of the recent advances in capsule architecture and routing mechanisms. In addition, we find that the relative focus in recent literature is on modifying routing procedure or architecture as a whole but the study of other finer components, specifically, squash function is wanting. Thus, we also present some new insights regarding the effect of squash functions in performance of the capsule networks. Finally, we conclude by discussing and proposing possible opportunities in the field of capsule networks.
