Skip to Main Content
 

Global Search Box

 
 
 

ETD Abstract Container

Abstract Header

Convolutional Neural Network Optimization Using Genetic Algorithms

Reiling, Anthony J.
http://orcid.org/0000-0003-3634-6292
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512662981172387

Abstract Details

2017, Master of Science in Computer Engineering, University of Dayton, Electrical and Computer Engineering.
This thesis proposes the use of a genetic algorithm (GA) to optimize the accuracy of a convolutional neural network (CNN). The GA modifies the structure of the CNN such as the number of convolutional filters, strides, kernel size, nodes, learning parameters, etc. Each modification of the network is trained and evaluated. Mutation of evolved networks create more successful networks over multiple generations. The final evolved network is 4.77% more accurate than a network pro- posed in the previous literature. Additionally, the evolved network is 13.4% less computationally complex.
Eric Balster (Advisor)
Tarek Taha (Committee Member)
Frank Scarpino (Committee Member)
42 p.
Artificial Intelligence; Computer Engineering; Computer Science
deep learning hyper parameter genetic algorithm evolutionary computation convolutional neural network optimization CNN DL GA CIFAR10

Recommended Citations

Citations

  • Reiling, A. J. (2017). Convolutional Neural Network Optimization Using Genetic Algorithms [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512662981172387

    APA Style (7th edition)

  • Reiling, Anthony . Convolutional Neural Network Optimization Using Genetic Algorithms. 2017. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512662981172387.

    MLA Style (8th edition)

  • Reiling, Anthony . "Convolutional Neural Network Optimization Using Genetic Algorithms." Master's thesis, University of Dayton, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512662981172387

    Chicago Manual of Style (17th edition)

dayton1512662981172387
6,377
© 2017, some rights reserved.Creative Commons License Convolutional Neural Network Optimization Using Genetic Algorithms by Anthony J. Reiling is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Dayton and OhioLINK.