Object Classifier in MATLAB® with Deep Learning Neural Networks

Authors

  • Allison Guzmán Lembo Universidad Autónoma de Nuevo León
  • Carlos Daniel Mayorga Alvarado Universidad Autónoma de Nuevo León
  • Jimena Fernanda Dávila Vázquez Universidad Autónoma de Nuevo León
  • Jonathan Martínez Reyna Universidad Autónoma de Nuevo León
  • Angel Rodriguez-Liñan Universidad Autónoma de Nuevo León https://orcid.org/0000-0002-0204-4424
  • Luis M. Torres-Treviño Universidad Autónoma de Nuevo León

DOI:

https://doi.org/10.29105/ingenierias24.90-16

Keywords:

Artificial neural network, deep learning, AlexNet, GoogLeNet, VGG-16, image recognition

Abstract

In this work, in an introductory way, the implementation of three pre-trained neural networks with the deep learning paradigm in MATLAB® software is illustrated, which can recognize objects in images captured by a camera. Through experiments to recognize objects, it was determined which of these networks performed better, taking advantage of a standard database of images. These results are illustrated with examples of the use of the software and comparative data of the hits.

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Author Biographies

Allison Guzmán Lembo, Universidad Autónoma de Nuevo León

Student of the Electronics and Automation Engineering career at the
Facultad de Ingeniería Mecánica y Eléctrica de la Universidad Autónoma de Nuevo León.

Carlos Daniel Mayorga Alvarado, Universidad Autónoma de Nuevo León

Professional Technical Bachelor in Industrial Electromechanics (2015) and currently a student of the Electronics and Automation Engineering career at the Facultad de Ingeniería Mecánica y Eléctrica de la Universidad Autónoma de Nuevo León.

Jimena Fernanda Dávila Vázquez, Universidad Autónoma de Nuevo León

Progressive Bilingual Technical Professional in Aeronautical Maintenance (2015) and student of the Electronics and Automation Engineer career at the Facultad de Ingeniería Mecánica y Eléctrica de la Universidad Autónoma de Nuevo León. She currently works in Automation at Schneider Electric.

Jonathan Martínez Reyna, Universidad Autónoma de Nuevo León

Student of the Electronics and Automation Engineering career at the Facultad de Ingeniería Mecánica y Eléctrica de la Universidad Autónoma de Nuevo León.

Angel Rodriguez-Liñan, Universidad Autónoma de Nuevo León

Engineer in Electronics and Communications (2003), Master in Electrical Engineering Sciences with a specialty in Control (2005) and Doctor in Electrical Engineering (2009) from FIME, UANL. He belongs to the Academic Body of Technology and Mechatronics Innovation. He is a professor at the Center for Innovation, Research and Development in Engineering and Technology. He obtained the UANL 2009 Research Award. Since 2011 he has been recognized by PRODEP and SNI.

Luis M. Torres-Treviño, Universidad Autónoma de Nuevo León

Mechanical Engineer, Master of Science and Doctorate in Materials Engineering from FIME-UANL. Post-doctorate at the University of Texas at Austin, USA. He is currently a research professor at FIME. Level II in the SNI.

References

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Published

2021-01-30

How to Cite

Guzmán Lembo, A., Mayorga Alvarado, C. D., Dávila Vázquez, J. F., Martínez Reyna, J., Rodriguez-Liñan, A., & Torres-Treviño, L. M. (2021). Object Classifier in MATLAB® with Deep Learning Neural Networks. Revista Ingenierías, 24(90), 41–54. https://doi.org/10.29105/ingenierias24.90-16