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Research Article

Arecanut Yield Disease Forecast using IoT and MachineLearning

  • Paper ID 10
  • Volume 1, Issue 2
  • Pages 06-08
  • Published Online: March-April 2021
  • 5 Views
Open Access Peer Reviewed

Authors

  • L. Vinod Kanan1
  • M. Sanjeev Kumar2

1,2Assistant Professor, Department of Computer Science & Engineering, Srinivas Institute of Technology, Mangaluru, India.

Article Information

DOI
No DOI
Published Online
March-April 2021
Pages
06-08
Article Type
Research Article
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No DOI available for cross-reference

References

1. HemantKumarWani,NilimaAshtankar“AnAppropriateModelPredictingPest/DiseasesofCropsUsingMachineLearningAlgorithms”,
International Conference on Advanced Computing and Communication Systems (ICACCS-2017), Jan 06-07, 2017.
2. Huu Quan Cap, Satoshi Kagiwada, Hiroyuki Uga, Hitoshi Iyatomi “A Deep Learning Approach for on-site Plant LeafDetection”,
International colloquium on Signal Processing and its applications (CSP A 2018), 9-10 March 2018.
3. G. Prem Rrishi Kranth, M. Hema Lalitha, Laharika Basava, Anjali Mathur “Plant Disease Prediction MachineLearning Algorithms”,
International Journal of Computer Applications (0975-8887), Volume 182-No.25, November-2018.
4. Adithya Khamparia, Gurinder Saini, Deepak Guptha, Ashish Khanna, Shrasti Tiwari, Victor Hugo C. de Albuquerque “Seasonal Crop
DiseasePredictionandClassificationUsingDeepConvolutionalEncoderNetwork”,Circuits,SystemsandSignalProcessing, Jan15,2019
5. R. D. Devi, S. A. Nandhini, R. Hemalatha and S. Radha, "IoT Enabled Efficient Detection and Classification of Plant Diseases for
Agricultural Applications," 2019 International Conference on Wireless Communications Signal Processing and Networking
(WiSPNET), Chennai, India,2019.
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