Deteksi Objek pada Citra Makanan Sebagai Rekomendasi Diet Menggunakan Metode Mask R-CNN
DOI:
https://doi.org/10.55606/juitik.v4i1.733Keywords:
Mask RCNN, Image, Food, AnnotationsAbstract
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%.
References
Abdulla, H., Ketzenberg, M., & Abbey, J. D. (2019). Taking stock of consumer returns: A review and classification of the literature. Journal of Operations Management, 65(6), 560–605. https://doi.org/10.1002/joom.1047
Apriyanti, L., Ismu, M. R., & Suseno, N. M. (2018). Aplikasi Mobile Pengelolaan Kalori Harian Untukpenderita Obesitas. Jurnal Teknologi Informasi Dan Komunikasi, 7(2), 16–23.
Bimanjaya, A., Handayani, H. H., & Darminto, M. R. (2021). Ekstraksi Tapak Bangunan dari Orthophoto Menggunakan Model Mask R-CNN (Studi Kasus: Kelurahan Darmo, Kota Surabaya). Jurnal Teknik ITS, 10(2). https://doi.org/10.12962/j23373539.v10i2.74747
Gede, P., & Cipta, S. (2020). Prediksi Citra Makanan Menggunakan Convolutional Neural Network Untuk. Jurnal Teknologi Informasi Dan Komputer, 30–38.
Muhammad Rizqi Zamzami, Dahnial, S., & Fitriyah, H. (2021). Sistem Identifikasi Jenis Makanan dan Perhitungan Kalori berdasarkan Warna HSV dan Sensor Loadcell menggunakan Metode K-NN berbasis. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 5(3), 936–942.
Setyaningsih, E. R., & Edy, M. S. (2022). YOLOv4 dan Mask R-CNN Untuk Deteksi Kerusakan Pada Karung Komoditi. Teknika, 11(1), 45–52. https://doi.org/10.34148/teknika.v11i1.419
Tyas, D. A., & Ratnaningsih, T. (2022). Analisis Segmentasi Sel Darah Merah berbasis Mask-RCNN. Journal of Informatics Information System Software Engineering and Applications (INISTA), 5(1), 1–7. https://doi.org/10.20895/inista.v5i1.766
Vainik, U., García-García, I., & Dagher, A. (2019). Uncontrolled eating: a unifying heritable trait linked with obesity, overeating, personality and the brain. European Journal of Neuroscience, 50(3), 2430–2445. https://doi.org/10.1111/ejn.14352
Wicaksono, A. (2021). Zebra Cross. Jurnal Teknis ITS, 10(2), 2337–3539.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Jurnal Ilmiah Teknik Informatika dan Komunikasi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.