CNN and Random Forest Hybrid Model for Tea Leaf Diseases Multiclassification

Tea leaf diseases constitute extremely hazardous to global tea production, impacting the final goods quantity as well as its quality. The paper includes an in-depth review of the extensive variety of diseases affecting tea crops, with a special focus on the root cause, distribution of wealth, as well as potential remedies of each disease. This paper uses the hybrid approach and data sizes. Convolutional neural networks, also called neural networks, comprise a form of artificially intelligent framework that is composed of an inner layer and a pooling layer. This feature boosts their efficacy. This update involves the use of a wide range of measures, including a median, age, preciseness, support, and recalls. The minimum accuracy in Class 3 is 0.94 and the maximum accuracy in Class 4 is 0.96. The macro average for precision is 85.12, recall is 84.98 and the F1-Score is 84.99 respectively. The weighted average for precision is 85.10, recall is 84.95 and F1-Score is 84.97 respectively. The Micro Average for precision, recall, and F1-Score is 84.95, 84.95, and 84.95 respectively. In this, is used 6 class. Farmers profit from it because this reduces time as well as money.