Journal
JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING
Volume 2019, Issue -, Pages -Publisher
HINDAWI LTD
DOI: 10.1155/2019/3217542
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Funding
- CAPES/Brazilian Ministry of Education Culture
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The choice of a good topology for a deep neural network is a complex task, essential for any deep learning project. This task normally demands knowledge from previous experience, as the higher amount of required computational resources makes trial and error approaches prohibitive. Evolutionary computation algorithms have shown success in many domains, by guiding the exploration of complex solution spaces in the direction of the best solutions, with minimal human intervention. In this sense, this work presents the use of genetic algorithms in deep neural networks topology selection. The evaluated algorithms were able to find competitive topologies while spending less computational resources when compared to state-of-the-art methods.
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