Fruits and vegetables calorie counter using Convolutional neural networks

Morteza Akbari Fard, Hamed Haddadi, Alireza Tavakoli Targhi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Individuals care about the types of fruit they are eating and the nutrients it contains because eating fruits and vegetables is an essential part of leading a healthy diet. In this paper we introduce an automatic way for detecting and recognizing the fruits in an image in order to enable keeping track of daily intake automatically using images taken by the user. The proposed method uses state of the art deep-learning techniques for feature extraction and classification. Deep learning methods, especially convolutional neural networks, have been widely used for a variety of classification problems and have achieved promising results. Our trained model has achieved an accuracy of 75% in the task of classification of 43 different types of fruit. The similar methods have achieved up to 70% with fewer classes.

Original languageEnglish
Title of host publicationDH 2016 - Proceedings of the 2016 Digital Health Conference
PublisherAssociation for Computing Machinery, Inc
Pages121-122
Number of pages2
ISBN (Print)9781450342247
DOIs
Publication statusPublished - 11 Apr 2016
Externally publishedYes
Event6th International Conference on Digital Health, DH 2016 - Montreal, Canada
Duration: 11 Apr 201613 Apr 2016

Other

Other6th International Conference on Digital Health, DH 2016
CountryCanada
CityMontreal
Period11/4/1613/4/16

Fingerprint

Vegetables
Fruits
Fruit
Neural networks
Eating
Learning
Nutrition
Nutrients
Feature extraction
Food
Deep learning

Keywords

  • Calorie counter
  • Convolutional neural network
  • Deep learning
  • Fruit classification
  • Fruit recognition

ASJC Scopus subject areas

  • Health Information Management
  • Computer Science Applications
  • Health Informatics

Cite this

Fard, M. A., Haddadi, H., & Targhi, A. T. (2016). Fruits and vegetables calorie counter using Convolutional neural networks. In DH 2016 - Proceedings of the 2016 Digital Health Conference (pp. 121-122). Association for Computing Machinery, Inc. https://doi.org/10.1145/2896338.2896355

Fruits and vegetables calorie counter using Convolutional neural networks. / Fard, Morteza Akbari; Haddadi, Hamed; Targhi, Alireza Tavakoli.

DH 2016 - Proceedings of the 2016 Digital Health Conference. Association for Computing Machinery, Inc, 2016. p. 121-122.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Fard, MA, Haddadi, H & Targhi, AT 2016, Fruits and vegetables calorie counter using Convolutional neural networks. in DH 2016 - Proceedings of the 2016 Digital Health Conference. Association for Computing Machinery, Inc, pp. 121-122, 6th International Conference on Digital Health, DH 2016, Montreal, Canada, 11/4/16. https://doi.org/10.1145/2896338.2896355
Fard MA, Haddadi H, Targhi AT. Fruits and vegetables calorie counter using Convolutional neural networks. In DH 2016 - Proceedings of the 2016 Digital Health Conference. Association for Computing Machinery, Inc. 2016. p. 121-122 https://doi.org/10.1145/2896338.2896355
Fard, Morteza Akbari ; Haddadi, Hamed ; Targhi, Alireza Tavakoli. / Fruits and vegetables calorie counter using Convolutional neural networks. DH 2016 - Proceedings of the 2016 Digital Health Conference. Association for Computing Machinery, Inc, 2016. pp. 121-122
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