An intelligent home access control system using deep neural network

Shih Hsiung Lee, Chu Sing Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In recent years, artificial intelligence technology has developed rapidly, and deep learning has been widely used in many areas. The performance of deep learning is particularly prominent in image recognition. This paper proposes a method to achieve efficient image recognition based on deep neural network using a small amount of data, which can be applied to home access control systems. The recognized objects include both pets and human faces. Through highly efficient training servers, inference models trained with data can be transferred to the embedded system. From the experimental results, we can see that the image recognition has a very good accuracy rate. It is feasible to apply artificial intelligence to consumer products and intelligent home access control systems.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages281-282
Number of pages2
ISBN (Electronic)9781509040179
DOIs
Publication statusPublished - 2017 Jul 25
Event4th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017 - Taipei, United States
Duration: 2017 Jun 122017 Jun 14

Publication series

Name2017 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017

Other

Other4th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017
CountryUnited States
CityTaipei
Period17-06-1217-06-14

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications
  • Signal Processing
  • Biomedical Engineering
  • Instrumentation
  • Electrical and Electronic Engineering

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  • Cite this

    Lee, S. H., & Yang, C. S. (2017). An intelligent home access control system using deep neural network. In 2017 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017 (pp. 281-282). [7991105] (2017 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-China.2017.7991105