A comprehensive classification of deep learning libraries

Pandey, Hari Mohan and Windridge, David ORCID: https://orcid.org/0000-0001-5507-8516 (2019) A comprehensive classification of deep learning libraries. In: International Congress on Information and Communication Technology, 27-28 Feb 2018, London, UK. (doi:10.1007/978-981-13-1165-9_40)

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Abstract

Deep Learning (DL) networks are composed of multiple processing layers that learn data representations with multiple levels of abstraction. In recent years, DL networks have significantly improved the state-of-the-art across different domains, including speech processing, text mining, pattern recognition, object detection, robotics and big data analytics. Generally, a researcher or practitioner who is planning to use DL networks for the first time faces difficulties in selecting suitable software tools. The present article provides a comprehensive list and taxonomy of current programming languages and software tools that can be utilized for implementation of DL networks. The motivation of this article is hence to create awareness among researchers, especially beginners, regarding the various languages and interfaces that are available to implement deep learning, and to provide a simplified ontological basis for selecting between them.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Proceedings published in the series: Advances in Intelligent Systems and Computing. Cite this paper as: Pandey H.M., Windridge D. (2019) A Comprehensive Classification of Deep Learning Libraries. In: Yang XS., Sherratt S., Dey N., Joshi A. (eds) Third International Congress on Information and Communication Technology. Advances in Intelligent Systems and Computing, vol 797. Springer, Singapore
Research Areas: A. > School of Science and Technology > Computer Science
A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 24430
Notes on copyright: This is a pre-copyedited version of a contribution published in Third International Congress on Information and Communication Technology: ICICT 2018, London, Editors: Yang, X-S., Sherratt, S., Dey, N., Joshi, A. (2019) published by Springer Nature. The definitive authenticated version is available online via https://doi.org/10.1007/978-981-13-1165-9_40
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Depositing User: Dr Hari Mohan Pandey
Date Deposited: 03 Jul 2018 10:21
Last Modified: 02 Oct 2019 09:45
ISBN: 9789811311642
URI: https://eprints.mdx.ac.uk/id/eprint/24430

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