A Machine Learning-Driven Approach for Early Leaf Disease Detection and Classification: A Survey
摘要
Mangifera Indica, popularly known as mangoes, is India’s highly important fruit crop. However, the widespread cultivation of mangoes in India exposes them and makes them vulnerable to different types of diseases, resulting in lower yield and economic losses. Anthracnose, Powdery Mildew, and Sooty Mould are the most common diseases that harm mango leaves. Many researchers have been working for control of disease on plants including mango trees to reduce loss of farmers’ production and indirectly reducing the stress levels for average mango farmers. The popular methodologies adopted by researchers are based on CNN. In the proposed sur vey work major challenges are covered to prevent diseases on mango trees. This study provides an in-depth examination of the strategies used to diagnose plant leaf diseases. It entails an investigation of several categorization systems useful for detecting plant leaf disease. Several scholars have made contributions to the topic, providing various ideas and implementations for recognising and managing plant leaf diseases.