Convolutional Neural Network and Capsule Neural Network: A Survey on architecture and applications

  • Arunkumar PM, M.Amala Jayanthi, R.Lakshmana Kumar
Keywords: NO KEYWORDS

Abstract

Convolutional neural network(ConvNet/CNN) and capsule neural network(CapsNet) are integral components of deep learning applications.Nowadays, Convolutional neural network based approach is used extensively in the broad spectrum of computer vision .Using simple computations ,the complex features are studied effectively by CNN architecture.But,of late, it has been observed that CNN has a very important pitfall of not considering the spatial relationship of data.This results in poor performance in certain applications. The deep learning research paradigm acquired a major break-through  ever since  the advent of Capsule networks.  These networks depend on  modelling the hierarchical relationships in perceiving  an image much similar to human brain. This paper explains the conceptual architecture and applications of both  ConvNet and CapsNet.The exploration of CapsNet and the subsequent results augurs well for the research community in imitating the human brain with much better accuracy.

Published
2021-08-04
How to Cite
R.Lakshmana Kumar, A. P. M. J. (2021). Convolutional Neural Network and Capsule Neural Network: A Survey on architecture and applications . Design Engineering, 6488- 6502. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/3146
Section
Articles