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What is A Comparative Analysis of Machine Learning Classifiers For Medicinal Plant Leaf Identification Using Image-Based Features about?

This study presents a comparative analysis of five machine learning classifiers for identifying medicinal plant species based on leaf images, utilizing image processing techniques such as CLAHE, median filtering, and k-means clustering. The Random Forest classifier achieved the highest accuracy of 93.80%, outperforming KNN, Naive Bayes, Decision Tree, and SVM. The findings highlight the effectiveness of the proposed methodology and suggest future improvements through additional feature integration and datas

Author

International Journal of Innovative Science and Research Technology

Language

EN