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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Diponegoro University
2018-07-01
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| Series: | Jurnal Teknologi dan Sistem Komputer |
| Subjects: | |
| Online Access: | https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13059 |
| _version_ | 1827337053933666304 |
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| author | Tri Septianto Endang Setyati Joan Santoso |
| author_facet | Tri Septianto Endang Setyati Joan Santoso |
| author_sort | Tri Septianto |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-07T18:45:17Z |
| format | Article |
| id | doaj.art-4a8733e6c0a147149ede6f450e4980c1 |
| institution | Directory Open Access Journal |
| issn | 2338-0403 |
| language | English |
| last_indexed | 2024-03-07T18:45:17Z |
| publishDate | 2018-07-01 |
| publisher | Diponegoro University |
| record_format | Article |
| series | Jurnal Teknologi dan Sistem Komputer |
| spelling | doaj.art-4a8733e6c0a147149ede6f450e4980c12024-03-02T02:42:46ZengDiponegoro UniversityJurnal Teknologi dan Sistem Komputer2338-04032018-07-016310610910.14710/jtsiskom.6.3.2018.106-10912751CNN LeNet Model for Year Digit Recognition on Relic Inscriptions of Majapahit KingdomTri Septianto0Endang Setyati1Joan Santoso2Sekolah Tinggi Teknik Surabaya, IndonesiaSekolah Tinggi Teknik Surabaya, IndonesiaSekolah Tinggi Teknik Surabaya, IndonesiaThe 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.https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13059kinerja rekognisi lenetpengenalan angka prasastiperbandingan kerja cnnkinerja rekognisi vgg |
| spellingShingle | Tri Septianto Endang Setyati Joan Santoso CNN LeNet Model for Year Digit Recognition on Relic Inscriptions of Majapahit Kingdom Jurnal Teknologi dan Sistem Komputer kinerja rekognisi lenet pengenalan angka prasasti perbandingan kerja cnn kinerja rekognisi vgg |
| title | CNN LeNet Model for Year Digit Recognition on Relic Inscriptions of Majapahit Kingdom |
| title_full | CNN LeNet Model for Year Digit Recognition on Relic Inscriptions of Majapahit Kingdom |
| title_fullStr | CNN LeNet Model for Year Digit Recognition on Relic Inscriptions of Majapahit Kingdom |
| title_full_unstemmed | CNN LeNet Model for Year Digit Recognition on Relic Inscriptions of Majapahit Kingdom |
| title_short | CNN LeNet Model for Year Digit Recognition on Relic Inscriptions of Majapahit Kingdom |
| title_sort | cnn lenet model for year digit recognition on relic inscriptions of majapahit kingdom |
| topic | kinerja rekognisi lenet pengenalan angka prasasti perbandingan kerja cnn kinerja rekognisi vgg |
| url | https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13059 |
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