An AI Based Approach for Medicinal Plant Identification and Classification Using Deep CNN

This paper introduces a novel Convolutional Neural Network (CNN) approach for predicting medicinal leaf types, aiming to enhance the accessibility of traditional medicinal plants. Identification of therapeutic plants is challenging, particularly for non-botanical experts. To address this, a meticulously curated dataset of medicinal leaf photos was prepared and processed. Subsequently, a CNN model was meticulously trained on this dataset, resulting in significantly improved accuracy compared to prior methods. This innovative approach shows promise in identifying medicinal leaves in their natural environments, thus supporting the preservation of traditional medical knowledge. Implementation involves stages such as dataset collection, model training, and real-world applications. The diverse dataset encompasses various leaves from medicinal plants treating fever, pain, and other ailments. This rich dataset facilitates the CNN model's learning to distinguish between different medicinal leaf varieties.