MEDIHERB INSIGHT

Abstract: Medicinal plants have been utilized for centuries in traditional medicine Known as Ayurveda. However, manual identification and classification of these plants are time-consuming and error-prone tasks. In this study, we introduce "MediHerb Insight," an automated system using deep learning techniques for the identification and classification of medicinal herbs. Through the implementation of a convolutional neural networks (CNN), specifically Xception Architecture, our model demonstrates impressive accuracy in classifying medicinal plant species based on leaf images. Additionally, we present a user-friendly web application that allows users to upload leaf images for instant classification. This project holds significance in advancing research in botany, providing a valuable tool for plant species identification and analysis.

Keywords: Medicinal Plants, Classification, Automated system, Deep learning techniques, Convolutional neural network (CNN),Xception architecture,Plant species identification.