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An Object-Oriented Neural Network Toolbox Based on Design Patterns

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Information and Software Technologies (ICIST 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 538))

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Abstract

Generally, the resolution of a problem by using soft-computing support requires several attempts for setting up a proper neural network. Such attempts consist of designing and training a neural network and can be a relevant effort for the developer. This paper proposes a toolbox that automates several steps for setting up a neural network, and provides high-level abstractions allowing a developer to choose classical network topologies and configure them as desired, as well as design a neural network from a scratch. A valuable aspect of our solution is given by the modularity of the whole design that builds on object-orientation and design patterns.

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Authors and Affiliations

  1. Department of Mathematics and Informatics, University of Catania, Viale Andrea Doria 6, 95125, Catania, Italy

    Christian Napoli & Emiliano Tramontana

Authors
  1. Christian Napoli
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  2. Emiliano Tramontana
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Correspondence to Christian Napoli .

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Editors and Affiliations

  1. Kaunas University of Technology, Kaunas, Lithuania

    Giedre Dregvaite

  2. Kaunas University of Technology, Kaunas, Lithuania

    Robertas Damasevicius

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Napoli, C., Tramontana, E. (2015). An Object-Oriented Neural Network Toolbox Based on Design Patterns. In: Dregvaite, G., Damasevicius, R. (eds) Information and Software Technologies. ICIST 2015. Communications in Computer and Information Science, vol 538. Springer, Cham. https://doi.org/10.1007/978-3-319-24770-0_34

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  • DOI: https://doi.org/10.1007/978-3-319-24770-0_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24769-4

  • Online ISBN: 978-3-319-24770-0

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