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International Conference on Image Processing and Communications

IP&C 2019: Image Processing and Communications pp 108–113Cite as

Initial Research on Fruit Classification Methods Using Deep Neural Networks

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1062))

Abstract

In the following paper, the methods from deep learning area, with the classical method of machine learning, have been compared. The fine-tuned networks: VGG, ResNet and MobileNet, as well as SVM, have been put together. Models of neural networks were trained using own dataset of fruit photos taken in laboratory conditions with the help of high-speed industrial cameras.

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Acknowledgement

This work was supported by the National Centre for Research and Development, project: Operational Programme Intelligent Development 2014–2020, edition: 5/1.1.1/2017.

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Authors and Affiliations

  1. Institute of Radioelectronics and Multimedia Technology, Warsaw University of Technology, Warsaw, Poland

    Zbigniew Nasarzewski

  2. Institiute of Microelectronics and Optoelectronics, Warsaw University of Technology, Warsaw, Poland

    Piotr Garbat

Authors
  1. Zbigniew Nasarzewski
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  2. Piotr Garbat
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Corresponding author

Correspondence to Zbigniew Nasarzewski .

Editor information

Editors and Affiliations

  1. Institute of Telecommunications and Computer Science, University of Science and Technology (UTP), Bydgoszcz, Poland

    Michał Choraś

  2. Department of Telecommunications, Computer Sciences and Electrical Engineering, University of Science and Technology (UTP), Bydgoszcz, Poland

    Ryszard S. Choraś

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Nasarzewski, Z., Garbat, P. (2020). Initial Research on Fruit Classification Methods Using Deep Neural Networks. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications. IP&C 2019. Advances in Intelligent Systems and Computing, vol 1062. Springer, Cham. https://doi.org/10.1007/978-3-030-31254-1_14

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