This study applies machine learning and image processing to classify plant leaf diseases by extracting color, texture, and shape features. Feature selection was performed using a Random Forest algorithm to identify the most important features. A Support Vector Machine (SVM) model, trained on the selected features, achieved 98.23% accuracy through hold-out validation. The results highlight the effectiveness of SVM in disease classification, promoting sustainable agriculture through technological innovation.
Link to the Dataset: https://data.mendeley.com/datasets/tywbtsjrjv/1
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