Java Plum Leaf Disease Dataset
Description
Description The Java Plum Leaf Disease Detection Dataset is a comprehensive collection of high-quality images of Java Plum leaves, designed to facilitate the development of robust Java Plum leaf disease detection systems using deep learning models. The dataset was meticulously gathered from two prominent areas in Cumilla, Bangladesh: Titas and Barura. It encompasses a diverse range of Java Plum leaf conditions encountered in real-world Java Plum cultivation, ensuring its practical relevance. Dataset Characteristics Origin: Titas and Barura, Cumilla, Bangladesh Image Type: Color photographs Image Resolution: Varies Number of Images: Adequate for training and testing deep learning models Number of Classes: 6 Bacterial_Spot Brown Blight Dry Healthy Powdery Mildew Sooty Mold Usage The Java Plum Leaf Disease Detection Dataset is primarily intended for developing and evaluating deep learning models for Java Plum leaf disease detection. It can also be used for various research purposes, such as analyzing the prevalence of different Java Plum leaf diseases and investigating the impact of environmental factors on leaf health. Significance The Java Plum Leaf Disease Detection Dataset is a valuable resource for advancing the field of precision agriculture in Bangladesh. By enabling the development of accurate Java Plum leaf disease detection systems, it has the potential to significantly enhance Java Plum cultivation practices, leading to increased productivity and reduced economic losses.