Plant Leaf Disease Detection Using Machine Learning

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Dr. A. Anjaiah, Abdul Aziz Syed, Manasa Thagirancha, Manasa Namala, Anusha Nayini


Our Problem Statement is potato plant disease identification using Convolutional Neural Networks and Keras. Now-a-days we can see various kinds of plant diseases which apparently causes high risk to In many regions of the world, it is still challenging to rapidly distinguish between farming and farmers. The field of leaf-based image classification is found to be very useful in emerging accurate techniques to solve this problem. In this project we used the Machine learning and Convolutional Neural Networks to distinguish in between the diseases namely Potato_Late_Blight and Potato_Early_Blight and Lefrom the data sets created. The phases of implementation for our project are dataset development, feature extraction, classifier training, and classification .Wetrained our dataset using CNNs. We also used Keras and Tensor flow to implement our model in CNN. Overall, we can clearly distinguish between the two diseases using machine learning and CNNs trained on publicly available data sets.

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