Identification of Ayurvedic Medicinal Plant Using Deep Learning

Abstract

Ayurvedic medicine is ancient medicine. This therapeutic approach makes use of plant materials that are used in Ayurvedic medicine. The plants need to be identified because they differ from the many  other plant species that can be found in nature. Without the proper knowledge, it could be difficult for the typical person to identify locally available herbal remedies. This demonstration shows a new technique that uses convolutional neural networks (CNN) and leaf images to identify the leaves of Ayurvedic medicinal plants. Computer technology advancements have allowed the field of computer vision to expand to include a wide range of applications. One of its applications is image classification, where it recognizes images more accurately than traditional methods. This document contains all of the information and direction needed to complete each step of the implementation process. All of the basic steps are covered in great detail, including building a database by gathering images and training models. Compared to other  methods, our deep neural network method yields a more accurate classification. Another benefit is easier feature extraction from the image, which can be fed into the model without requiring preprocessing. One way to feed deep convolutional neural networks    is with raw photo data. Without needing to extract the leaves themselves, we can precisely classify leaves using deep neural networks, which capture and store visual properties as an image moves through several layers. Web applications and deep learning are used to sort and present worksheets. The deep learning technology used in this essay is the convolutional  neural network.