A Study on the Generation of Datasets for Applied AI to OLED Life Prediction

• 발행기관: 한국인공지능학회
• 저자명: Myung-Ae CHUNG Dong Hun HAN Seongdeok AHN Min Soo KANG
• 간행물 정보: 『인공지능연구』Vol.10 No. 2, 7~11쪽, 전체 5쪽
• 주제분류: 복합학 > 과학기술학
• 파일형태: PDF
• 발행일자: 2022.12.31

영문 초록

OLED displays cannot be used permanently due to burn-in or generation of dark spots due to degradation. Therefore, the time when the display can operate normally is very important. It is close to impossible to physically measure the time when the display operates normally. Therefore, the time that works normally should be predicted in a way other than a physical way. Therefore, if you do computer simulations based on artificial intelligence, you can increase the accuracy of prediction by saving time and continuous learning. Therefore, if we do computer simulations based on artificial intelligence, we can increase the accuracy of prediction by saving time and continuous learning. In this paper, a dataset in the form of development from generation to diffusion of dark spots, which is one of the causes related to the life of OLED, was generated by applying the finite element method. The dark spots were generated in nine conditions, such as 0.1 to 2.0 μm with the size of pinholes, the number was 10 to 100, and 50% with water content. The learning data created in this way may be a criterion for generating an artificial intelligence-based dataset.

키워드

OLED Dataset Bigdata AI Machine learning