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All Journal Jurnal Ilmiah Teknik Informatika dan Komunikasi
Fitriyah Hidayati
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Computer Science & IT Electrical & Electronics Engineering

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Deteksi Objek pada Citra Makanan Sebagai Rekomendasi Diet Menggunakan Metode Mask R-CNN Ratri Enggar Pawening; Meliana Eka Puteri; Agmelita Dwi Jianika; Fitriyah Hidayati
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 4 No. 1 (2024): Maret : Jurnal Ilmiah Teknik Informatika dan Komunikasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v4i1.733

Abstract

Food is one of the main needs in life for survival. This is because the energy the body needs for activities and body metabolism is obtained by consuming food. Therefore, consuming food can maintain body health and the body's metabolism can work well. In this study, the aim was to detect objects in food images, namely the types of food such as fried chicken, hamburger, seblak, baso aci, and bakwan. The method used for object detection is Mask RCNN. Previously, the image will be pre-processed, namely the resizing and annotation process. The research results show that object detection in food images has an accuracy of 72%.
Co-Authors Agmelita Dwi Jianika Meliana Eka Puteri Ratri Enggar Pawening