Plant Leaf Disease Detection Using Deeplearning and CNN

Plant Leaf Disease Detection Using Deep Learning And CNN

Prof. Mithuna H R, Praveenkumar K V, Rashmitha, Shwetha M, Sinchana

STUDENTS OF DEPARTMENT INFORMATION SCIENCE AND ENGINEERING

ACHARYA INSTITUTE OF TECHNOLOGY, SOLADEVANAHALLI. 560107

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Abstract - The suggested technology aids in the detection of plant disease and provides a remedy that will be used as a defence against the disease. The information found on the internet is fascinatingly hidden, so unique plant species are identified and given new names in order to build a reliable database of data. This database then contains a variety of plant diseases that are used to assess the enterprise's accuracy and level of confidence. Then, using data from coaching tasks, we will train our classifier to produce results with the highest accuracy possible. We frequently employ a convolutional neural network called the FASTER CNN, which has various layers utilised for prediction.This project offers a method for identifying diseases from images of plant leaves using Tensor Flow, an object identification API. The model was trained to use a quicker RCNN approach. Additionally, the accuracy value is determined. Our information processing system learning strategy learns often and could be easier in plant disease investigation when given a large amount of education and an outstanding sample of datasets.