Application Development for a Project using Flutter

Plant disease detection consumes more time and money for farmers and also manual detection errors may also lead to low crop cultivation rate. The proposed study has used the YOLO V3 demonstration with a transfer learning approach to identify the infections in photos of betel leaves. To significantly increase betel leaf cultivation, the diseases should be identified at an early stage before it spreads to the entire field. The proposed betel leaf disease detection strategy accomplishes a proper balance of exactness and recognition speed. The parameters of the suggested demonstration were adjusted for the classification task, and a high level of precision of around 95.6% was attained.