FACE RECOGNITION SYSTEM FOR SINGLE-BOARD COMPUTERS BASED ON MACHINE LEARNING METHODS

Authors

  • Nikita Kolmakov MIREA - Russian Technological University https://orcid.org/
  • Alexey Rusakov MIREA - Russian Technological University https://orcid.org/

DOI:

https://doi.org/10.30888/2415-7538.2021-21-01-027

Keywords:

neural networks, python, googlenet, vgg19, resnet50, single-board computer, jetsonnano, visualization, face recognition.

Abstract

The paper considers the result of learning machine learning model architectures: GoogLeNet, ResNet50, and VGG19. Also in the framework of the work, the visualization of the training of each architecture and the comparison of their performance will be exam

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References

Voulodimos A. et al. Deep learning for computer vision: A brief review //Computational intelligence and neuroscience. – 2018. – Т. 2018.

NVIDIA JETSON NANO // URL: https://www.nvidia.com/ru-ru/autonomous-machines/embedded-systems/jetson-nano/ (дата обращения: 10.04.2021).

NVIDIA Jetson Nano T208 Power Management Board with 6-cell 18650 UPS // URL: https://a.aliexpress.com/_Afk2ef (дата обращения: 10.04.2021).

Used Image’s DataSet // URL: https://vk.cc/c1b2TC (дата обращения: 10.04.2021).

PYTORCH DOCUMENTATION // URL: https://pytorch.org/ (дата обращения: 10.04.2021).

Keras & TensorFlow // URL: https://keras.io/ (дата обращения: 10.04.2021).

ImageNet image database // URL: http://image-net.org/ (дата обращения: 10.04.2021).

STREAMLIT DOCUMENTATION // URL: https://streamlit.io/ (дата обращения: 10.04.2021).

Published

2021-04-30

How to Cite

Колмаков, Н., & Русаков, А. (2021). FACE RECOGNITION SYSTEM FOR SINGLE-BOARD COMPUTERS BASED ON MACHINE LEARNING METHODS. Scientific Look into the Future, 1(21-01), 50–63. https://doi.org/10.30888/2415-7538.2021-21-01-027

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