Multi-Class Medicinal Plant Leaf Classification Recognition and Recommendation System Using DNN

This project develops an automated system for classifying medicinal leaves from different species using DNNs and providing medicinal recommendations based on the classification. CNNs are used to process images of leaves, identifying species by detecting unique features. The model was trained on a varied dataset of labeled medicinal plant leaves, achieving high accuracy in species identification. Additionally, a recommendation system was incorporated to connect the identified species with their medicinal uses. This work enhances the process of medicinal plant identification, offering a scalable and automated solution that can be expanded with more data and used in healthcare and research applications.