| 한글제목(Korean Title) |
엣지 TPU 기반의 임베디드 기기별 경량화된 이미지 분류 모델 비교 |
| 영문제목(English Title) |
Comparison of Lightweight Image Classification Model by Embedded Device Based on Edge TPU |
| 저자(Author) |
최동현
김남현
고상근
이수안
Donghyeon Choi
Namhyeon Kim
Sangkeun Ko
Suan Lee
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| 원문수록처(Citation) |
VOL 45 NO. 01 PP. 2162 ~ 2164 (2022. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
AIoT is emerging as it moves from the IT era of the tertiary industry to the fourth industrial revolution. AIoT equipment requires00 lightweight model of deep learning because of its limited performance. In this paper, a comparative study was conducted on the time required for inference of lightweight deep learning model on Edge TPU environment equipment optimized for artificial intelligence, and a significant speed difference could be confirmed. Using the results of this paper, it will help build an AIoT environment using Edge TPU. |
| 키워드(Keyword) |
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| 파일첨부 |
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