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Performance Evaluation of VegeCare Tool for Tomato Disease Classification

  • Natwadee Ruedeeniraman
  • Makoto IkedaEmail author
  • Leonard Barolli
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1036)

Abstract

The aged population in Japan is increased and some people start to work in agriculture after the retirement. Therefore, it is important to teach the skills to these agricultural beginners. Also, to improve the productivity of vegetables, advanced approaches based on Artificial Intelligence (AI) and sensing technology are needed. We focus on vegetable recognition using Deep Neural Network (DNN) as a method to visualize the knowledge in vegetable production. In this paper, we present the performance evaluation of VegeCare tool for tomato disease classification. We used 6 kinds of tomato diseases. The plant disease classification is one of the functions of the proposed VegeCare tool, which helps the growth of vegetables for farmers. The evaluation results show that the learning accuracy was more than 90%. We found that the tomato disease classification results was selected correctly for the tomato mosaic virus.

Keywords

Plant disease classification VegeCare Tomato disease DNN 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Natwadee Ruedeeniraman
    • 1
  • Makoto Ikeda
    • 2
    Email author
  • Leonard Barolli
    • 2
  1. 1.Graduate School of EngineeringFukuoka Institute of TechnologyFukuokaJapan
  2. 2.Department of Information and Communication EngineeringFukuoka Institute of TechnologyFukuokaJapan

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