• DocumentCode
    3089209
  • Title

    The Transmittance Estimation of Touch Panel Decoration Film by Neural Network

  • Author

    Huang, Du-Jou ; Liu, Fang-Tsung ; Chuang, Shang-Jen ; Chen, Yu-Ju ; Wang, Shuming T. ; Hwang, Rey-Chue

  • Author_Institution
    Electr. Eng. Dept., I-Shou Univ., Dashu, Taiwan
  • fYear
    2010
  • fDate
    17-19 Sept. 2010
  • Firstpage
    940
  • Lastpage
    943
  • Abstract
    In this paper, a transmittance estimator of touch panel decoration film by using neural network is presented. In the evaporation process, the coating material and the related control parameters are all important influencing factors in obtaining the desired transmittance. The relationship among the transmittance and these factors are very complex and nonlinear. It´s very hard to use the certain mathematical model to describe such relationship. In this research, the neural network was employed to catch the relationship among transmittance and its possible influencing factors. In other words, an efficiently and precisely automatic evaporation parameters decision system for touch panel decoration film is expected to be developed. Through the estimation system developed, the quality of transmittance of touch panel film could meet the customer´s requirement.
  • Keywords
    coatings; neural nets; touch sensitive screens; vacuum deposition; automatic evaporation parameters decision system; evaporation process; mathematical model; neural network; touch panel decoration film; transmittance estimation; Artificial intelligence; Artificial neural networks; Coatings; Estimation; Films; Process control; Training; decoration film; estimator; neural network; transmittance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-8043-2
  • Electronic_ISBN
    978-0-7695-4180-8
  • Type

    conf

  • DOI
    10.1109/PCSPA.2010.232
  • Filename
    5635932