This paper presents the chromatic aberration identification of touch panel (TP) decoration film by using nearly equivalent neural network (NN) model. This model is expected to adequately catch the complex relationship between the chromatic aberration and its possible influencing factors during the evaporation process of TP decoration film. Then, an intelligent estimator for the chromatic aberration of TP film could be developed automatically. Based on this estimator, the technician could set the control parameters of evaporation process in advance and make the quality of chromatic aberration of TP could meet the customer’s required.
The chromatic aberration estimations of touch panel (TP) film by using neural networks are presented in this paper. The neural networks with error back-propagation (BP) learning algorithm were used to catch the complex relationship between the chromatic aberration, i.e., L.A.B. values, and the relative parameters of TP decoration film. An artificial intelligent (AI) estimator based on neural model for the estimation of physical property of TP film is expected to be developed. From the simulation results shown, the estimations of chromatic aberration of TP film are very accurate. In other words, such an AI estimator is quite promising and potential in commercial using.
In this paper, the chromatic aberration estimator of touch panel (TP) decoration film by using neural network is presented. Through the training of neural network, the complex relationship between the chromatic aberration and the parameters of evaporation process of TP decoration film is expected to be found. Thus, an intelligent decision mechanism for the chromatic aberration of TP film on its evaporation process could be developed. Based on this mechanism, the technician could set the control parameters of evaporation in advance so that the quality of chromatic aberration of TP could meet the customer’s request.
This research aims to estimate the optical property of touch panel (TP) with different layers coating. The neural network (NN) model is used to catch the complex relationship among the chromatic aberration, i.e. L. a. b. values, and their relevant influencing factors. An artificial intelligent (AI) estimator is expected to be developed so that the optical property of TP decoration film with different layers coating could be precisely estimated before the evaporation process is taken. Such an AI estimator can help the technician to set the control parameters of evaporator in advance and make the films optical property could fit the customers request. From the simulation results shown, the estimations of chromatic aberration of TP film are very accurate. In other words, such an AI estimator is possibly to be developed and it is quite promising and potential in the real industrial applications.
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