Development of Machine Learning Model for Medicinal Plant Identification

Accurate identification of medicinal plants is of paramount importance in pharmaceutical research, traditional medicine, and conservation efforts. This work presents the development of a machine learning model for the identification of medicinal plants. A comprehensive standard image of diverse medicinal plant species were collected and preprocessed for model training and evaluation. The model development process involved training and fine-tuning a deep CNN architecture on the medicinal plant dataset. Data augmentation techniques were employed to enhance the model's generalization and robustness. The trained model demonstrated impressive accuracy and effectiveness in identifying medicinal plants, achieving high classification performance across different species with diverse morphological variations and characteristics.