An Automatic System for Medicinal Plant Identification Using ResNet- CNN

Medicinal plant classification is crucial to preserve traditional knowledge and formulate natural medicine with fewer side effects. Here, we propose an automatic medicinal plant classification using deep learning techniques. Our approach utilizes convolutional neural networks (CNNs) to classify over different types of medicinal plants based on leaf images in an efficient manner. The model classifies different medicinal plants based on leaf images. The image processing system uses the threshold method in order to remove unwanted pixels to have a clean dataset to be processed by the CNN. The model not only categorizes plant species but also offers elaborate information regarding their medicinal benefits, making it easy for users to determine the indigenous medicinal application of plants. Moreover, the model examines combinations of plants to propose possible synergies among various medicinal plants to assist in herbal medicine preparation. It offers knowledge on how combining certain plants can increase therapeutic efficacy, leading to a more effective and synergistic natural medicine. This system is anticipated to fill the knowledge gap on medicinal plants and their uses by modern generations and therefore promote the use of traditional remedies in contemporary healthcare practices.