P‐106: A Based Machine Learning Model for the Prediction of Initial Gamma Values for OLED Panels
Gamma tuning is an important step in producing high‐quality OLED panels; in order to ensure the quality of OLED panels, OLED panels usually need 9 to 12 gamma curves at one frequency, covering the entire brightness range of the panel. And there are several adjusting nodes (generally 15~27) on each g...
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Published in | SID International Symposium Digest of technical papers Vol. 55; no. 1; pp. 1788 - 1789 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Campbell
Wiley Subscription Services, Inc
01.06.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Gamma tuning is an important step in producing high‐quality OLED panels; in order to ensure the quality of OLED panels, OLED panels usually need 9 to 12 gamma curves at one frequency, covering the entire brightness range of the panel. And there are several adjusting nodes (generally 15~27) on each gamma curve. The current gamma tuning needs to calibrate each node through external optical equipment and stores them in the display IC. However, the initial values of the register adjusted by the current method is less accurate. The method is proposed for gamma values prediction based on machine learning that improves accuracy greatly. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 0097-966X 2168-0159 |
DOI: | 10.1002/sdtp.17923 |