Development of a Platform for Generation of CNN and Multilayer Neural Networks

Authors

  • Daniel Marcelo González-Arriaga Benemérita Universidad Autónoma de Puebla
  • María Aurora Diozcora Vargas-Treviño Benemérita Universidad Autónoma de Puebla
  • Josefina Guerrero García Benemérita Universidad Autónoma de Puebla
  • Jesús López Gómez Universidad Juárez Autónoma de Tabasco

DOI:

https://doi.org/10.13053/cys-26-1-4162

Keywords:

CNN, multilayer, software, platform, Lab-VIEW platform, MATLAB platform

Abstract

This research presents the design of a platform that assists in the generation of convolutional (CNN) and multilayer neural networks to provide a user-friendly interface for the design, formation, and development of neural networks. This platform is developed in LabVIEW as this software allows to perform inter-faces and generate an executable for use. It aims to reduce the development time of neural networks by providing an assistant-like graphical interface that guides the user through various common scenarios (data import, neural network construction and adjustment), allows the user to focus on solving their problems without having to write code, edit text files, or manually analyze recorded data. The user interface with the options offered is described. The way the neural network is generated is described. The results generated with the platform are presented producing an image with the proposed methodology applying a complete convolution layer. The usefulness of this platform is explained by presenting a case where there is a significant improvement in the development of a neural network, in time and reduction of errors.

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Published

2022-03-26

Issue

Vol. 26 No. 1 (2022): Recent Advances in Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez, D. Vilariño)

Section

Articles of the Thematic Issue

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