Precise Recognition of Medicinal Plants using Xception Architecture

The growing demand for automatic and precise recognition of medicinal plants, coupled with the potential techniques of deep learning, prompted us to investigate the use of CNN architectures. Especially Inception, to accurately categorize the different types of medicinal plants according to their leaves. This study looks at the recognizing different medicinal plants' leaves using deep learning methods, specifically a primitive architecture of convolutional neural networks (CNN). The study makes use of a wealth of data, including 6,900 high resolution images of 80 distinct types of medicinal plants. The main goal is to advance the field of medicinal plant identification by creating a reliable model that accurately identifies plant species. The results of this study demonstrate the potential of deep learning, especially the initial architecture, to solve complex and subtle botanical identification problems and make important contributions to the field of medicinal plant identification.