Evaluating Deep Neural Networks for the Classification and Identification of Medicinal Plant Species

It is essential to comprehend medicinal plant species in order to safeguard and preserve biodiversity. These plants require complex, intensive processes for their classification and identification, which are usually overseen by botanical specialists. The goal of this systematic review is to provide a comprehensive assessment of earlier studies on the use of deep learning methods for the identification and categorization of species of medicinal plants. By revolutionizing plant classification, deep neural networks (DNNs) have made substantial advancements in crop yield protection and agricultural risk management. Eight therapeutic plants are recognized and categorized in the suggested system with the use of DNN models, and important assessment metrics including F1 score, recall, accuracy, and precision are also calculated. This method produces subtle insights that make it easier to distinguish between therapeutic plants.