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Fruit Calories Estimation using Convolutional Neural Network

Authors:

Analyn N Yumang,

Dave Emilson S Banguilan,

Clark Kent S VeneracionAuthors Info & Claims

ICBET '23: Proceedings of the 2023 13th International Conference on Biomedical Engineering and Technology

Pages 231 - 235

https://doi.org/10.1145/3620679.3620720

Published: 19 December 2023 Publication History

Abstract

A fit person who is health conscious always considers weighing what they eat and takes the calories on the food they eat. There is a certain number of calories per day that helps bodybuilders or people who want to stay fit. Taking in considerations of eating Fruits to have the calories, macros and nutrients they need. This study presents fruit calorie estimation using CNN or Convolutional Neural Network, the program was able to detect all the fruits with recognition accuracy of 70% and the percentage difference calorie estimation for each fruit are as follows: apple has 30.58%, banana garnered 21.15%, grapes garnered 44.07% and orange has 32.20%.

References

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Digital Library

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T. Ege, Y. Ando, R. Tanno, W. Shimoda and K. Yanai, "Image-Based Estimation of Real Food Size for Accurate Food Calorie Estimation," 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), 2019, pp. 274-279.

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S. Sasano, X. Han and Y. Chen, "Food recognition by combined bags of color features and texture features," 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2016, pp. 815-819. BMEI.2016.7852822.

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Cited By

S SBenjamin R(2024)Enhancing Nutrition Tracking: Webcam-Based Fruit and Vegetable Recognition and Calorie Measurement Using Image Processing and Convolutional Neural Networks2024 5th International Conference for Emerging Technology (INCET)10.1109/INCET61516.2024.10593554(1-7)Online publication date: 24-May-2024
https://doi.org/10.1109/INCET61516.2024.10593554
Priscilla MSuriya ASrikanth JJagadhishwaran SKumar MYasvanth D(2024)Evolution of Artificial Intelligence Based Burned Calories Prediction System Using Novel Hybrid Learning Methodology2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)10.1109/ICONSTEM60960.2024.10568726(1-7)Online publication date: 4-Apr-2024
https://doi.org/10.1109/ICONSTEM60960.2024.10568726

Index Terms

Fruit Calories Estimation using Convolutional Neural Network
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification

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cover image ACM Other conferences

ICBET '23: Proceedings of the 2023 13th International Conference on Biomedical Engineering and Technology

June 2023

271 pages

ISBN:9798400707438

DOI:10.1145/3620679

Copyright © 2023 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 December 2023

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ICBET 2023

ICBET 2023: 2023 13th International Conference on Biomedical Engineering and Technology

June 15 - 18, 2023

Tokyo, Japan

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Cited By

S SBenjamin R(2024)Enhancing Nutrition Tracking: Webcam-Based Fruit and Vegetable Recognition and Calorie Measurement Using Image Processing and Convolutional Neural Networks2024 5th International Conference for Emerging Technology (INCET)10.1109/INCET61516.2024.10593554(1-7)Online publication date: 24-May-2024
https://doi.org/10.1109/INCET61516.2024.10593554
Priscilla MSuriya ASrikanth JJagadhishwaran SKumar MYasvanth D(2024)Evolution of Artificial Intelligence Based Burned Calories Prediction System Using Novel Hybrid Learning Methodology2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)10.1109/ICONSTEM60960.2024.10568726(1-7)Online publication date: 4-Apr-2024
https://doi.org/10.1109/ICONSTEM60960.2024.10568726

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