Abstract:
Correct drugs should be administered in ealing ith the disease appropriately. Since allopathic medicine accelerates relief, it is not meant to deal radically with the root causes of disease manifestation. Ayurvedic drugs take steps directed at the root cause by establishing long-term solutions to restore health holistically. Accurate identification and classification of these plants represent a key factor for improving Ayurvedic medicinal products in modern health care delivery. It deals with the concern of classification and identification of Ayurvedic medicinal plants using advanced deep learning techniques. In this case, we utilized the methodology of Convolutional Neural Networks (CNNs), which analyze image data about medicinal plants, thereby allowing accurate classification to take place. This paper also integrates several methods-FCM clustering and H-Gabor filters-for enhanced feature extraction and segmentation. By taking a comprehensive Medicinal Plant Data set, the approach facilitates identification and promotes the better usage of Ayurvedic resources. Some conclusions drawn from the conducted research on plant-based medicine, incorporating traditional knowledge, open prospects for future innovations for improvement.
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