메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술대회자료
저자정보
Hyun-Jun Park (Pai Chai University) Kyounghee Lee (Pai Chai University)
저널정보
한국정보통신학회 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING 2019 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING Vo.11 No.1
발행연도
2019.6
수록면
240 - 243 (4page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

이 논문의 연구 히스토리 (2)

초록· 키워드

오류제보하기
This paper describes a web server implementation providing an artificial intelligence platform to enable users to easily build and run their own intelligent applications. With our implementation, a user can run a web server and utilize web-based services with various functionalities of Tensorflow. A user can create and manage a project to deal with an artificial neural network which is basically provided by the web server or a newly designed by the user. Unlike the existing artificial intelligence applications designed for specific purposes such as object or face recognition, the proposed system enables users to design their own neural network models dealing with various types of data depending on their needs. It is also provided as a web-based open server platform which can be easily connected to the other platforms to relay the results of learning such as inference and classification. Using the proposed platform, we have designed a simple object recognition model and implemented an application based on the model. With the application, we demonstrated that the proposed platform provides operability and propriety for the required functions. The further study could be to add web-based library module which can be easily used for wider areas and more diverse purposes.

목차

Abstract
I. INTRODUCTION
II. PROPOSED SYSTEM ARCHITECTURE
III. IMPLEMENTATION RESULTS
IV. CONCLUSION
REFERENCES

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2019-004-000919481