Avaliação do Processo para Embarcar uma Rede Neural Baseada em YOLO Utilizando um Acelerador de Hardware Dedicado

  • Isabel Costa IFCE
  • Elias Silva Jr IFCE
  • Antônio Rodrigues IFCE
  • Leandro Angeloni IFCE
  • Edmilson Dias IFCE

Resumo


Object Detection is a challenging task in computer vision, but Deep Neural Networks (DNN) have made great progress in this area. This work presents the process and the results obtained in the attempts to embed a YOLO V3 model in a Neural Compute Engine, the Movidius Stick. Experiments were carried out with a Tensorflow model that is converted to Movidius (using OpenVINO) including an evaluation of the Movidius stick connected to a Raspberry Pi3. The application uses aerial images of power distribution towers captured by a drone. Although there are some fully operational networks for Neural Compute Engines, there are some difficulties in porting new networks to the platform, with gains in performance, but with losses in accuracy.

Palavras-chave: Sistemas Embarcados, Deep-Learning, Acelerador de Hardware.

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A. Pester and M. Schrittesser, “Object detection with raspberry pi3 and movidius neural network stick,” in 2019 5th Experiment International Conference (exp.at’19), 2019, pp. 326–330.
Publicado
23/11/2020
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COSTA, Isabel; SILVA JR, Elias; RODRIGUES, Antônio; ANGELONI, Leandro; DIAS, Edmilson. Avaliação do Processo para Embarcar uma Rede Neural Baseada em YOLO Utilizando um Acelerador de Hardware Dedicado. In: TRABALHOS EM ANDAMENTO - SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SISTEMAS COMPUTACIONAIS (SBESC), 10. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 174-179. DOI: https://doi.org/10.5753/sbesc_estendido.2020.13109.