Tea Leaf Diseases Classification and Detection using a Convolutional Neural Network
Vishesh Tanwar, Shweta Lamba
Abstract
It is worth noting the fact that tea is the most popular drink on the planet and India is one of the top producers and consumers of it. However, many diseases that affect crop quality and yield can interfere with tea production. Machine learning techniques such as deep learning are making it easier to identify and classify these diseases in tea leaves. The presence of disease symptoms in tea leaves can be used to classify and identify various diseases using deep learning techniques such as Convolutional Neural Networks (CNN). This strategy helps detect disease early and maintain good health. Both of these are essential to sustainable agricultural practices. As manual detection can be time-consuming and require specialized personnel, applying image processing models can greatly aid in identifying diseases in a large number of tea leaves. A proposed study using CNN layers classified submitted photos into one of his eight categories with a staggering 96% accuracy.