Plant Disease Detection using Deep Learning and Convolutional Neural Network

Authors

  • Kavipriya L, Priyadharsini R, Soma Prathibha

Abstract

                  Deep learning methods are greatly admired in the research field of agriculture. The fundamental basic key aspect of agriculture is soil for crop growing.The proposed system identifies the plant disease and provide remedies that can be used as a defence mechanism against the disease..The data is divided into training data and testing data. The data is trained with the classifier and then output is  predicted with optimum accuracy. The Convolution Neural Network (CNN) which comprises of different layers which are used for prediction. And also prediction of  the name of the crops that can be cultivatable to their corresponding soil types.

A system is designed which can be used for large agricultural fields images of the plants which will act as input for the software, based on which the software will tell us whether the plant is healthy or not. With the code and training model we have achieved an accuracy level of 78% .The system  gives us the plant species disease with its confidence level and also the remedy that can be taken as a cure.

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Published

2020-05-18

Issue

Section

Articles