Image recognition in the artificial agriculture officer

  • Authors

    • B Lokesh
    • Ravoori Charishma
    • Natuva Hiranmai
    2018-06-21
    https://doi.org/10.14419/ijet.v7i3.3.14500
  • Android application, Artificial agriculture officer, Convolutional Neural Networks, Image Recognition, Tensor flow.

  • Abstract

    Farmers face a multitude of problems nowadays such as lower crop production, tumultuous weather patterns, and crop infections. All of these issues can be solved if they have access to the right information. The current methods of information retrieval, such as search engine lookup and talking to an Agriculture Officer, have multiple defects. A more suitable solution, that we are proposing, is an android application, available at all times, that can give succinct answers to any question a farmer may pose. The application will include an image recognition component that will be able to recognize a variety of crop diseases in the case that the farmer does not know what he is dealing with and is unable to describe it.  Image recognition is the ability of a computer to recognize and distinguish between different objects, and is actually a much harder problem to solve than it seems. We are using Tensorflow, a tool that uses convolutional neural networks, to implement it

     

     

  • References

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  • How to Cite

    Lokesh, B., Charishma, R., & Hiranmai, N. (2018). Image recognition in the artificial agriculture officer. International Journal of Engineering & Technology, 7(3.3), 119-121. https://doi.org/10.14419/ijet.v7i3.3.14500

    Received date: 2018-06-21

    Accepted date: 2018-06-21

    Published date: 2018-06-21