FRUIT DISEASE DETECTION USING IMAGE PROCESSING

Abstract

This study will use a technique to identify fruit-related illnesses and even identify specific disease
kinds that target fruits based on similarities. Because of this, the method makes use of CNNs (Convolutional
Neural Networks), a deep learning algorithm that is most frequently used to analyze visual imagery. The
algorithm takes in images as input and uses various aspects and parameters to differentiate the images. Farmers
will undoubtedly benefit from this in the near future since it will improve crop growth. Python has been selected
for further examination in this technique. The accuracy level attained by using the suggested approach is 99%.