International Journal of Scientific Research and Engineering Development

The identification of medicinal plants is crucial for their conservation and utilization in healthcare and pharmaceutical applications. Traditional methods of plant recognition are often time-consuming and prone to errors, highlighting the need for an automated approach. This project addresses the problem by leveraging machine learning and image processing techniques for accurate medicinal plant recognition. A deep learning-based model, specifically a Convolutional Neural Network (CNN), is trained on plant images to classify species based on their visual features. The methodology involves image preprocessing, augmentation, and model optimization to improve classification accuracy. Experimental results demonstrate the effectiveness of deep learning in medicinal plant recognition, contributing to biodiversity conservation and the advancement of herbal medicine research.