Optimization of a Convolutional Neural Network Using a Hybrid Algorithm

Chia Ling Huang, Yan Chih Shih, Chyh Ming Lai, Vera Yuk Ying Chung, Wen Bo Zhu, Wei Chang Yeh, Xiangjian He

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

In recent years, Convolutional Neural Networks (CNNs) have been widely used in image recognition due to their aptitude in large scale image processing. The CNN uses Back-propagation (BP) to train weights and biases, which in turn makes the error consistently smaller. The most common optimizers that uses a BP algorithm are Stochastic Gradient Decent (SGD), Adam, and Adadelta. These optimizers, however, have been proved to fall easily into the regional optimal solution. Little research has been conducted on the application of Soft Computing in CNN to fix the above problem, and most studies that have been conducted focus on Particle Swarm Optimization. Among them, the hybrid algorithm combined with SGD proposed by Albeahdili improves the image classification accuracy over that achieved by the original CNN. This study proposes the amalgamation of Improved Simplified Swarm Optimization (iSSO) with SGD, hence culminating in the iSSO-SGD which is intended train CNNs more efficiently to establish a better prediction model and improve the classification accuracy. The performance of the proposed iSSO-SGD can be affirmed through a comparison with the PSO-SGD, the Adam, Adadelta, rmsprop and momentum optimizers and their abilities in improving the accuracy of image classification.

Original languageEnglish
Title of host publication2019 International Joint Conference on Neural Networks, IJCNN 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728119854
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes
Event2019 International Joint Conference on Neural Networks, IJCNN 2019 - Budapest, Hungary
Duration: 14 Jul 201919 Jul 2019

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2019-July

Conference

Conference2019 International Joint Conference on Neural Networks, IJCNN 2019
Country/TerritoryHungary
CityBudapest
Period14/07/1919/07/19

Keywords

  • Convolutional Neural Network
  • Image Recognition
  • Improved Simplified Swarm Optimization
  • Stochastic Gradient Decent

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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