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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Kade Bramasta Vikana Putra
Udayana University
Computer Science & IT Engineering

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Klasifikasi Citra Daging Menggunakan Deep Learning dengan Optimisasi Hard Voting Kade Bramasta Vikana Putra; I Putu Agung Bayupati; Dewa Made Sri Arsa
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 4 (2021): Agustus 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (616.603 KB) | DOI: 10.29207/resti.v5i4.3247

Abstract

Meat is a staple food for some Indonesian people, apart from the taste, meat also contains vitamins and minerals that are good for the human body, however, not all meat can be consumed by the Indonesian people. the texture and color of beef, pork and mutton have similarities and tend to be similar, therefore a system is needed to recognize the three types of meat. In this study, the authors use various types of Deep Learning architecture such as Resnet-50, VGG-16, VGG-19 and Densenet-121 with Hard Voting to improve the performance of Deep Learning in recognizing the three types of meat. The results show that Resnet-50 with Hard Voting can outperform Deep Learning Resnet-50, VGG-16, VGG-19 and Densenet-121- with f1 score 98.88%, precision 98.89% and recall 98.88%. in image classification of pork, beef and mutton.
Co-Authors Arsa, Dewa Made Sri I Putu Agung Bayupati