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  2. Volume 7, Issue 7
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Online ISSN: 2515-8260

Volume7, Issue7

A Literature Review on Detection of Plant Diseases

    Prof. A. R. Bhagat Patil Lokesh Sharma Nishant Aochar Rajat Gaidhane Vikas Sawarkar Dr Punit Fulzele Dr. Gaurav Mishra

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 7, Pages 1605-1614

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Abstract

With increase in population the need for food is on rise, in such circumstances, plant diseases prove to be a major threat to agricultural produce and result in disastrous consequences for farmers. Early detection of plant disease can help in ensuring food security and controlling financial losses. The images of diseased plants can be used to identify the diseases. Classification abilities of Convolutional Neural Networks are used to obtain reliable output. Google’s pretrained model ‘Inception v3’ is used. The Inception v3 model is trained over a dataset of diseased plants obtained from ‘Plant Village Dataset’. The developed detection approach is evaluated on measures of F1 score, precision and recall.
Keywords:
    plant disease Image processing image acquisition segmentation Feature Extraction Classification
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(2020). A Literature Review on Detection of Plant Diseases. European Journal of Molecular & Clinical Medicine, 7(7), 1605-1614.
Prof. A. R. Bhagat Patil; Lokesh Sharma; Nishant Aochar; Rajat Gaidhane; Vikas Sawarkar; Dr Punit Fulzele; Dr. Gaurav Mishra. "A Literature Review on Detection of Plant Diseases". European Journal of Molecular & Clinical Medicine, 7, 7, 2020, 1605-1614.
(2020). 'A Literature Review on Detection of Plant Diseases', European Journal of Molecular & Clinical Medicine, 7(7), pp. 1605-1614.
A Literature Review on Detection of Plant Diseases. European Journal of Molecular & Clinical Medicine, 2020; 7(7): 1605-1614.
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