A CNN Model Based Approach for Disease Detection in Mango Plant Leaves

In this study, we propose a machine learning (ML) based method for the early detection of plant leaf diseases. Plant diseases are a major concern in agriculture, impacting crop yield, and food security. Early and accurate identification of these diseases is vital for effective disease management. Our approach employs deep learning algorithms and a dataset of annotated images containing both healthy and diseased plant leaves. Through training a deep neural network, we enable automated disease detection by extracting relevant features from leaf images and classifying them as healthy or diseased. By reducing reliance on human expertise, our approach enables timely detection, facilitating prompt implementation of disease management strategies. This ML-based method has the potential to revolutionize the field of plant pathology, offering valuable insights for the development of precision agriculture techniques aimed at ensuring sustainable crop production.