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@article{ART002795102},
author={Jae-Hyeok Jeong and Jinman Jung and Yun Young-Sun},
title={Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture},
journal={Journal of Software Assessment and Valuation},
issn={2092-8114},
year={2021},
volume={17},
number={2},
pages={161-172},
doi={10.29056/jsav.2021.12.17}

TY - JOUR
AU - Jae-Hyeok Jeong
AU - Jinman Jung
AU - Yun Young-Sun
TI - Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture
JO - Journal of Software Assessment and Valuation
PY - 2021
VL - 17
IS - 2
PB - Korea Software Assessment and Valuation Society
SP - 161
EP - 172
SN - 2092-8114
AB - Neuromorphic architecture is drawing attention as a next-generation computing that supports artificial intelligence technology with low energy. However, FPGA embedded boards based on Neuromorphic architecturehave limited resources due to size and power. In this paper, we compared and evaluated the image reduction method using the interpolation method that rescales the size without considering the feature points and the DCT (Discrete Cosine Transform) method that preserves the feature points as much as possible based on energy. The scaled images were compared and analyzed for accuracy through CNN (Convolutional Neural Networks) in a PC environment and in the Nengo framework of an FPGA embedded board.. As a result of the experiment, DCT based classification showed about 1.9% higher performance than that of interpolation representation in both CNN and FPGA nengo environments. Based on the experimental results, when the DCT method is used in a limited resource environment such as an embedded board, a lot of resources are allocated to the expression of neurons used for classification, and the recognition rate is expected to increase.
KW - Neuromorphic architecture;Discrete Cosine Transform;Image Reduction;Embedded Neuromorphic Boards
DO - 10.29056/jsav.2021.12.17
ER -

Jae-Hyeok Jeong, Jinman Jung and Yun Young-Sun. (2021). Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture. Journal of Software Assessment and Valuation, 17(2), 161-172.

Jae-Hyeok Jeong, Jinman Jung and Yun Young-Sun. 2021, "Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture", Journal of Software Assessment and Valuation, vol.17, no.2 pp.161-172. Available from: doi:10.29056/jsav.2021.12.17

Jae-Hyeok Jeong, Jinman Jung, Yun Young-Sun "Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture" Journal of Software Assessment and Valuation 17.2 pp.161-172 (2021) : 161.

Jae-Hyeok Jeong, Jinman Jung, Yun Young-Sun. Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture. 2021; 17(2), 161-172. Available from: doi:10.29056/jsav.2021.12.17

Jae-Hyeok Jeong, Jinman Jung and Yun Young-Sun. "Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture" Journal of Software Assessment and Valuation 17, no.2 (2021) : 161-172.doi: 10.29056/jsav.2021.12.17

Jae-Hyeok Jeong; Jinman Jung; Yun Young-Sun. Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture. Journal of Software Assessment and Valuation, 17(2), 161-172. doi: 10.29056/jsav.2021.12.17

Jae-Hyeok Jeong; Jinman Jung; Yun Young-Sun. Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture. Journal of Software Assessment and Valuation. 2021; 17(2) 161-172. doi: 10.29056/jsav.2021.12.17

Jae-Hyeok Jeong, Jinman Jung, Yun Young-Sun. Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture. 2021; 17(2), 161-172. Available from: doi:10.29056/jsav.2021.12.17

Jae-Hyeok Jeong, Jinman Jung and Yun Young-Sun. "Feature Representation Method to Improve Image Classification Performance in FPGA Embedded Boards Based on Neuromorphic Architecture" Journal of Software Assessment and Valuation 17, no.2 (2021) : 161-172.doi: 10.29056/jsav.2021.12.17