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FedSnM: P2P 네트워크에서 효율적인 통신을 위한Score-and-Model 방식을 활용한 연합학습
- 박성환;
- 이재우
초록
A digital twin is a technology that creates a virtual world identical to the real world. Problems in the real world can be identified through various simulations, so it is a trend to be applied in various industries. In order to apply the digital twin, it is necessary to analyze the drawings in which the structure of the real world to be made identical is designed. Although the technology for analyzing drawings is being studied, it is difficult to apply them because the rules or standards for drawing drawings are different for each author. Therefore, in this paper, we implement a system that analyzes and classifies the vertex detail, one of the drawings, using artificial intelligence. Through this, we intend to confirm the possibility of analyzing and classifying drawings through artificial intelligence and introduce future research directions.
키워드
- 제목
- FedSnM: P2P 네트워크에서 효율적인 통신을 위한Score-and-Model 방식을 활용한 연합학습
- 제목 (타언어)
- FedSnM: Score-and-Model based Communication-Efficient Federated Learning in Peer-to-Peer Network Environment
- 저자
- 박성환; 이재우
- 발행일
- 2023-02
- 저널명
- 한국정보통신학회논문지
- 권
- 27
- 호
- 2
- 페이지
- 1809 ~ 1815
- 언어
- KOR
- 출판사
- 한국정보통신학회
- 발행국가
- 대한민국
- 분량
- 7 페이지
- ISSN
- E 2288-4165
P 2234-4772