인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
DL(Deep Learning) has been applied to various tasks, and image classification is one of the most active areas where DL is applied. While the majority of DL approaches have focused on achieving improvements in classification accuracy by innovating a network structure with standard datasets in low resolution, detailed features in a high-resolution dataset are crucial to enhance classification accuracy, especially for practical datasets in the industry. We proposed a DL classifier structure that fully utilizes high-definition information for an OLED (Organic Light-Emitting Diode) panel inspection, and, for verification, we performed the task of classifying the authenticity of the actual OLED panel defects. The authenticity inspection of panel defects requires a precise analysis of high-resolution information. We confirmed that the application of the proposed classifier structure improved the performance of the classification. The proposed method includes an object detection method optimized for panel inspection and displays stable performance by utilizing an ensemble structure. The proposed method has been applied and is being used in actual production lines.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2021-003-001917492