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All Journal Pixel : Jurnal Ilmiah Komputer Grafis Journal of Information Systems Engineering and Business Intelligence JURNAL MEDIA INFORMATIKA BUDIDARMA JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURIKOM (Jurnal Riset Komputer) Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Building of Informatics, Technology and Science Jurnal Mantik Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal E-Komtek JIKA (Jurnal Informatika) Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Jurnal Teknik Informatika (JUTIF) Teknika Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan IJCOSIN : Indonesian Journal of Community Service and Innovation KREATIF: Jurnal Pengabdian Masyarakat Nusantara Jurnal Informatika Jurnal Masyarakat Madani Indonesia eProceedings of Engineering Jurnal Informatika: Jurnal Pengembangan IT Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Jnanadharma Transaction on Informatics and Data Science Jurnal Teknokes KREATIF: Jurnal Pengabdian Masyarakat Nusantara
Yohani Setiya Rafika Nur
Telkom University
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Journal : Jurnal Teknokes

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Food Detection to Estimate Calories Using Detection Transformer Kristanto, Joshua Putra Fesha; Prabowo, Dedy Agung; Yohani Setiya Rafika Nur
Jurnal Teknokes Vol. 18 No. 4 (2025): Desember
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jteknokes.v18i4.132

Abstract

Accurately estimating calorie intake remains a common challenge, as many individuals have limited understanding of portion sizes and the caloric content of foods. This lack of nutritional knowledge is a major cause of both over- and under-calorie consumption and contributes to significant public health problems, including obesity, cardiovascular disease, and chronic metabolic disorders. Although computer vision–based approaches for dietary assessment have advanced, many methods still rely on handcrafted features, anchor-based CNN detectors, or controlled geometric assumptions. This indicates a practical gap in developing a fully functional system that operates on basic RGB images captured under everyday conditions. This study aims to develop an end-to-end food detection and calorie estimation system using the Detection Transformer (DETR) to predict calorie values directly from food images. The main contributions of this study include: (1) employing DETR to address non-maximum suppression limitations and improve the stability of multi-food recognition; (2) using a bounding box area-to-weight ratio as a low-complexity alternative to segmentation-based food portion estimation; and (3) developing a user-friendly interface for output visualization that displays detected food items and their estimated calorie values in real-world scenarios involving irregular food shapes and varying focal lengths. A DETR-based detector was trained using 2,228 COCO-formatted images across six distinct food classes. Calorie values were estimated by predicting food weight based on bounding box measurements, followed by calorie calculation using standardized reference weights. The method assessed robustness by evaluation on both controlled and real-life food images. Experimental results demonstrated moderate performance, with 0.617 mean Average Precision (mAP) and 0.656 mean Average Recall (mAR). The weight prediction module served as the primary estimation component, achieving a mean absolute residual of 8.7. These findings suggest that bounding box area is a reliable estimator of serving size. This study serves as a proof of concept for monitoring individual food intake and provides a foundation for further improvement in sub-item recognition, three-dimensional volume estimation, and the inclusion of broader food classes.
Co-Authors Adanti Wido Paramadini Ade Prasetyo, Ade Adriano, Riftian Dimas Afifatul Fajri, Nabila Ajeng Dyah Kurniawati Al Faiz, M. Hanif Alfonsus Simbolon Alika, Shintia Dwi Amalia Beladinna Arifa Aminatus Sa’adah Andre Citro Febriliyan Lanyak Audrey Hillary Auliya Burhanuddin Azmi, Wifqi Wifakul Bachrul Restu Bagja Bidayatul Masulah Bita Parga Zen Christantie Effendy Christian Tambunan, Gerry Claudio Felle, Roland Dading Qolbu Adi Dasril Aldo Dedi Rahman Habibie Dedy Agung Prabowo Deni Romadan, Muhamad Dwi Putro Wicaksono, Aditya Edelin Gultom Endraswari, Putri Mentari Eryan Ahmad Firdaus Faisal Dharma Adhinata Faiz, M. Hanif Al Fathan, Faizal Burhani Ulil Fau, Andrew Filfimo Yulfiz Ahsanul Hulqi Firmansyah, Muhammad Raafi'u Gusla Nengsih, Yeyi Gusnita Linda Hasan, Faiz Hidayat, Afifah Naurah Imam Ghozali J. Manurung, Barnes Kristanto, Joshua Putra Fesha Lina Fatimah Lishobrina Luqman Wahyudi M Yoka Fathoni Maulana, Ihsan Maulana, ⁠Ihsan Melinda Br Ginting Miftahul Ilmi Muadin, Dika Alim Muhamad Azrino Gustalika Nadia Ayu Isroh Nia Annisa Ferani Tanjung Nur Ghaniaviyanto Ramadhan Nurhaeka Tou Pamuji, Yanuar Ikhsan Paradise Ramadhani, Rima Dias Rania Nur Hikmah Rianto Putra, Frederick Ridho Rahmadi Sa'adah, Aminatus Sahara Sahara Sapta Eka Putra Sulaeman, Gilang Suprapto, Amelia Rut Suryani, Ajeng Ayu Syahputra, Dio Trihastuti Yuniati Ummi Athiyah Usman, Muhammad Lulu Latif Utami, Annisaa Wahyu Adi Prabowo Wanda Ilham Warto Widya Lelisa Army Yasin, Feri Yehezekiel Ramasyah Putra Haloho Yoka Fathoni, M. Yuan Sa'adati Zahirah, Regina Putri Wanda