Current Result Document :
| 한글제목(Korean Title) |
CAN 데이터 기반 압축 딥러닝 모델 연구 |
| 영문제목(English Title) |
A Study on Compression Deep Learning Model based on CAN Data |
| 저자(Author) |
백장현
노용철
장수현
Jang-Hyun Baek
Yong-Cheol Noh
Soo-Hyun Jang
노용철
백장현
신대교
장수현
Yong-Cheol Noh
Jang-Hyun Baek
Dae-kyo Shin
Soo-Hyun Jang
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| 원문수록처(Citation) |
VOL 45 NO. 01 PP. 1998 ~ 2001 (2022. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
In this paper, we compare compressor with rule based and deep learing based algorithms. Deep learing based compressors are Trace and Dzip model, rule based compressors are LZMA, bz2, zlib. We use Controller Area Network data from a automobile. we find deep learing compressors are better than rue based compressor. In particular, Dzip compressor is the best performenance in Saving Space.
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| 키워드(Keyword) |
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| 파일첨부 |
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