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Achieving an optimal group structure in a neural architecture search
- Seo, W.;
- Park, J.;
- Lim, W.;
- Kim, Dae-Won;
- Lee, Jaesung
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0초록
The method proposed in this letter searches for an effective group structure of group convolutions in a convolutional neural network that can improve the classification accuracy. The model's group structure is obtained using an effective differential neural architecture search. Our code can be accessed at https://github.com/minercode625/grunas.git. © 2022 The Authors. Electronics Letters published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
- 제목
- Achieving an optimal group structure in a neural architecture search
- 저자
- Seo, W.; Park, J.; Lim, W.; Kim, Dae-Won; Lee, Jaesung
- 발행일
- 2022-09
- 유형
- Article
- 권
- 58
- 호
- 19
- 페이지
- 732 ~ 733
- 언어
- ENG
- 출판사
- John Wiley and Sons Inc
- 발행국가
- 영국
- 분량
- 2 페이지
- ISSN
- E 1350-911X
P 0013-5194