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  Published Paper Details:

  Paper Title

NEURAL NETWORK BASED PLANT LEAF DISEASE DETECTION

  Authors

  S.KISHORE KUMAR,  Dr.G.MAMATHA

  Keywords

Convolutional Neural Networks, Convolution, Pooling, GoogLeNet, Confusion matrix

  Abstract


Farmers have large range of diversity for selecting various suitable crops and finding the suitable pesticides for plant. Disease on plant leads to the significant reduction in both the quality and quantity of agricultural products. Earlier detection of problems by Adapting to the latest technologies which provide automated processing through machine learning provides a better way for sustainable farming. It is very difficult to monitor the plant diseases manually. It requires tremendous amount of work, expertize in the plant diseases, and also require the excessive processing time. Hence, image processing is used for the detection of plant diseases. The proposed solution improves the system performance and detect damages on leafs accurately. In this paper mainly focuses on three steps, feature extraction, classification and identifying the disease. The experimental result compared and shows better than other methods

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2104171

  Paper ID - 205668

  Page Number(s) - 1349-1358

  Pubished in - Volume 9 | Issue 4 | April 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  S.KISHORE KUMAR,  Dr.G.MAMATHA,   "NEURAL NETWORK BASED PLANT LEAF DISEASE DETECTION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 4, pp.1349-1358, April 2021, Available at :http://www.ijcrt.org/papers/IJCRT2104171.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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