Litchi Leaf Disease Multiclasssification: Unraveling the Enigma Using CNN-Random Forest Model

This study examines the effect of diseases in litchi leaves and fruit. It recognizes which type of disease affects the litchi fruit and leaves. In paper, displays the different diseases and the solution of these diseases. We use different technology to solve the problem of diseases. We use the CNN approach to finding the data and the data size is 5087 it has been conducted in the Punjab area. The micro average has been achieved with 92.16% accuracy, the Macro average has been achieved with 92.11% accuracy and the Weighted average has achieved 92.20% accuracy. The paper used a multi-class (6-class) classification model to find accurate and reliable results. It displays the number of instances from various classes that were correctly predicted. This paper will help the farmer to find the diseases at the right time and it will also help to resolve the disease from which production of litchi will increase day by day. It saves time and cost for the farmers to find the diseases. This finding is useful for the farmer and in the future, In future, can use other CNN approaches to find more accurate and reliable results.