메뉴 건너뛰기
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)
고객센터 ENG
주제분류

논문 기본 정보

저자정보
(Wuhan Business University)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.14 No.1
오류 신고하기

피인용 0

검색

    초록·키워드

    The lack of interactive guidance in the art self-learning process is currently the main problem that learners face, which often makes it difficult to continue learning. To solve this problem, the study designs an interactive art teaching system. This system is based on the iOS system and is primarily aimed at art beginners. The instructional system and learners participate in educational exchanges using the iOS painting image style classification model. Further, the system realizes interaction between students through the painting description generation model. This process facilitates intra-platform interaction. The results shows that the classification accuracy of the designed painting image style classification model is above 80.00%, and the average recall rate is 78.16%. In addition, the designed painting description generation models are accurate in the range of 84.45% to 97.74%, and the recall rate is in the range of 83.71% to 98.27%. The study demonstrates the effectiveness of the interactive art teaching system for providing guidance to beginner in the art department.

    최근 본 자료 전체보기

      UCI(KEPA) : I410-151-25-02-092302843