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Explorations into Deep Learning Mobile Applications

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Intelligent Human Systems Integration (IHSI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 722))

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Abstract

This paper presents a feasibility study into a deep learning image recognition system that is embedded into a prototype mobile test-bed application designed to help users maintain healthy eating habits. A natural multimodal interaction is favored allowing a user to take photos of the food ingredients she has at her disposal for preparing a meal. The application utilizes the image recognition system to recognize a variety of fruits, vegetables and other food products as a basis for suggesting well-balanced dietary alternatives. The paper presents our initial explorations with several convolutional neural networks (CNNs) architectures of varying depth and structure. We compare the recognition accuracies and performance of different combinations of the model hyper-parameters complemented with few data augmentation techniques.

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Notes

  1. 1.

    http://www.supercook.com/#/recipes.

  2. 2.

    https://play.google.com/store/apps/details?id=com.garagedevs.foodies&hl=en.

  3. 3.

    http://www.image-net.org/.

  4. 4.

    https://keras.io/.

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Acknowledgments

This research was partially funded by the Faculty of Computer Science and Engineering, University of “Ss. Cyril and Methodius”, Macedonia.

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Authors and Affiliations

  1. Faculty of Computer Science and Engineering, Ruger Boskovikj 16, 1000, Skopje, Macedonia

    Alisa Krstova, Alek Petreski & Sonja Gievska

Authors
  1. Alisa Krstova
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  2. Alek Petreski
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  3. Sonja Gievska
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Corresponding author

Correspondence to Sonja Gievska .

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Editors and Affiliations

  1. University of Central Florida, Orlando, Florida, USA

    Waldemar Karwowski

  2. University of Central Florida, Orlando, Florida, USA

    Tareq Ahram

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Krstova, A., Petreski, A., Gievska, S. (2018). Explorations into Deep Learning Mobile Applications. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-73888-8_66

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  • DOI: https://doi.org/10.1007/978-3-319-73888-8_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73887-1

  • Online ISBN: 978-3-319-73888-8

  • eBook Packages: EngineeringEngineering (R0)

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