IMPLEMENTATION SOLUTIONS FOR DEEP LEARNING NEURAL NETWORKS TARGETING VARIOUS APPLICATION FIELDS

Dana-Mihaela Petroşanu () and Alexandru Pîrjan ()
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Dana-Mihaela Petroşanu: University Politehnica of Bucharest, Bucharest, Romania
Alexandru Pîrjan: Romanian-American University, Bucharest, Romania

Journal of Information Systems & Operations Management, 2017, vol. 11, issue 1, 155-169

Abstract: In this paper, we tackle important topics related to deep learning neural networks and their undisputed usefulness in solving a great variety of applications ranging from image and voice recognition to business related fields where they have the potential to bring significant financial benefits. The implementations and scale sizes of deep learning neural networks are influenced by the requirements of the developed artificial intelligence (AI) applications. We are focusing our research on certain application fields that are most suitable to benefit from the deep learning optimized implementations. We have analyzed and compared the most popular deep learning libraries available today. Of particular interest was to identify and analyze specific features that must be taken into account for in accordance with the tasks that have to be solved.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:rau:jisomg:v:11:y:2017:i:1:p:155-169

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