CNN LeNet Model for Year Digit Recognition on Relic Inscriptions of Majapahit Kingdom

The object of the inscription has a feature that is difficult to recognize because it is generally eroded and faded. This study analyzed the performance of CNN using LeNet model to recognize the object of year digit found on the relic inscriptions of Majapahit Kingdom. Object recognition with LeNet...

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Bibliographic Details
Main Authors: Tri Septianto, Endang Setyati, Joan Santoso
Format: Article
Language:English
Published: Diponegoro University 2018-07-01
Series:Jurnal Teknologi dan Sistem Komputer
Subjects:
Online Access:https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13059
Description
Summary:The object of the inscription has a feature that is difficult to recognize because it is generally eroded and faded. This study analyzed the performance of CNN using LeNet model to recognize the object of year digit found on the relic inscriptions of Majapahit Kingdom. Object recognition with LeNet model had a maximum accuracy of 85.08% at 10 epoch in 6069 seconds. This LeNet's performance was better than the VGG as the comparison model with a maximum accuracy of 11.39% at 10 epoch in 40223 seconds.
ISSN:2338-0403