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  • 标题:Image Classification of Golek Puppet Images using Convolutional Neural Networks Algorithm
  • 本地全文:下载
  • 作者:Tuti Purwaningsih ; Triano Nurhikmat ; Pertiwi Bekti Utami
  • 期刊名称:International Journal of Advances in Soft Computing and Its Applications
  • 印刷版ISSN:2074-8523
  • 出版年度:2019
  • 卷号:11
  • 期号:1
  • 页码:34-45
  • 出版社:International Center for Scientific Research and Studies
  • 摘要:Golek puppet is traditional art that developed in Indonesia especially in West Java province. Golek puppet has become one of entertainment for West Java people. But in this era, many people has forget about golek puppet. It causes the youth generation starting to leave about this culture. One of the reason why this can be happened is golek puppet has to many category and it makes hard to remember all of them. With the number of Golek puppet category, the classification of category Golek puppet automatically is needed through recognition of Golek puppet image. Deep learning can be used to recognize Golek puppet images. The best method to classifying image is using Convolutional Neural Network (CNN). This study resulted accuracy with CNN method in amount of 100% accuracy to classifying Golek puppet image. Which can be decided as the best method in classifying image.
  • 关键词:Deep Learning; Image Classification; Golek Puppet; Accuracy; Convolutional Neural Networks
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