Identification and Classification of Medicinal Plants using Deep Learning

For medicinal plants to be used effectively in pharmaceutical research, healthcare, and biodiversity conservation, they must be accurately identified and classified. Conventional plant identification techniques take a lot of time, call for specialized knowledge, and are prone to human error. With an emphasis on image-based plant recognition, this study suggests an automated classification system for medicinal plants utilizing machine learning techniques. A carefully selected dataset of photos of medicinal plants is used to train a convolutional neural network (CNN), which then learns unique visual characteristics for precise classification. Users can upload plant photos for real-time identification using the user-centric web application with authentication features included in the suggested system. To enhance model performance and generalization, image preprocessing methods like augmentation, normalization, and resizing are used. The model’s ability to differentiate between different species of medicinal plants is demonstrated by the high classification accuraccy of thee experimental results.