P‐2.1: A LSTM‐based Deep Learning Model for the Prediction of Initial Register Values in IC Modules in the Process of Gamma Tuning for OLED Panels

This paper proposes a novel LSTM model for precise prediction of initial register value in OLED Gamma tuning. Usually the bottleneck of Gamma tuning speed depends on the accuracy of initial register value prediction in IC modules for each bind point. By utilizing the long short‐term memory character of LSTM, high prediction accuracy is achieved which greatly shrink the search time for register value, thus reducing the overall average tuning time for each bind point of OLED screens and enhancing the amounts of adjusted screens per unit time in autonomous pipelines.