CROP LEAF DISEASE DETECTION WITH FERTILIZER RECOMMENDATION USING CNN ALGORITHM

Early Disease Detection and pets are vital for higher yield and high-satisfactory of crops. With Reduction in Quality of the rural Product, Disease Plant can result in the big Economic Losses to the Individual farmers. In USA like India whose primary Population is worried in Agriculture It could be very vital to discover the sickness at early stages. Faster and precise prediction of plant sickness ought to assist decreasing the losses. With the Significant development and trends in Deep studying have given the Opportunity to enhance the overall performance and accuracy of detection of item and popularity system. This Paper, specializes in locating the plant illnesses and decreasing the financial losses. We have proposed the deep leaning primarily based totally technique for photograph popularity. We have tested the 3 predominant Architecture of the Neural Network: Faster Region-primarily based totally Convolution Neural Network (Faster R-CNN), Region-primarily based totally Fully CNN(R-CNN) and Single shot Multibook Detector (SSD). System proposed withinside the paper can detect the distinct forms of sickness correctly and feature the cap potential to deal with complicated scenarios. And also extend the approach to recommend the fertilizers based on severity analysis with measurements. Validation end result display the accuracy of 94.6% which depicts the feasibility of Convolution Neural Network and gift the direction for AI primarily based totally Deep Learning Solution to this Complex Problem.