Hybrid Algorithm for the Optimization of Training Convolutional Neural Network
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2015, Vol 6, Issue 10
Abstract
The training optimization processes and efficient fast classification are vital elements in the development of a convolution neural network (CNN). Although stochastic gradient descend (SGD) is a Prevalence algorithm used by many researchers for the optimization of training CNNs, it has vast limitations. In this paper, it is endeavor to diminish and tackle drawbacks inherited from SGD by proposing an alternate algorithm for CNN training optimization. A hybrid of genetic algorithm (GA) and particle swarm optimization (PSO) is deployed in this work. In addition to SGD, PSO and genetic algorithm (PSO-GA) are also incorporated as a combined and efficient mechanism in achieving non trivial solutions. The proposed unified method achieves state-of-the-art classification results on the different challenge benchmark datasets such as MNIST, CIFAR-10, and SVHN. Experimental results showed that the results outperform and achieve superior results to most contemporary approaches.
Authors and Affiliations
Hayder Albeahdili, Tony Han, Naz Islam
Keywords
Related Articles
- EP ID EP106528
- DOI 10.14569/IJACSA.2015.061011
- Views 130
- Downloads 0
Hospital Queue Control System using Quick Response Code (QR Code) as Verification of Patient’s Arrival
Hospital is an organization that primarily provides services in the form of examination, treatment, medical treatment and other diagnostic measures required by each patient in the limits of the technology and the means p...
Missing Data Imputation using Genetic Algorithm for Supervised Learning
Data is an important asset for any organization to successfully run its business. When we collect data, it contains data with low qualities such as noise, incomplete, missing values etc. If the quality of data is low the...
Development of Prediction Model for Endocrine Disorders in the Korean Elderly Using CART Algorithm
The aim of the present cross-sectional study was to analyze the factors that affect endocrine disorders in the Korean elderly. The data were taken from the A Study of the Seoul Welfare Panel Study 2010. The subjects were...
A Novel Edge Cover based Graph Coloring Algorithm
Graph Colouring Problem is a well-known NP-Hard problem. In Graph Colouring Problem (GCP) all vertices of any graph must be coloured in such a way that no two adjacent vertices are coloured with the same colour. In this...
Optimizing the Hyperparameter of Feature Extraction and Machine Learning Classification Algorithms
The process of assigning a quantitative value to a piece of text expressing a mood or effect is called Sentiment analysis. Comparison of several machine learning, feature extraction approaches, and parameter optimization...