Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9976
Title: Medicinal Plants Detection Using ML and DL
Authors: Guleria, Ayush
Gandotra, Ekta [Guided by]
Keywords: Medicinal plants
Machine learning
World health organization
Convolutional neural networks
Issue Date: 2023
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: Traditional medicine has used medicinal plants for ages as all-natural treatments for a wide range of illnesses. They include medicinal bioactive substances that can be utilized to treat a variety of ailments. The identification and characterisation of medicinal plants are of increasing importance due to the rising demand for natural products and the requirement for sustainable healthcare. Based on their physical and chemical features, machine learning (ML) and deep learning (DL) algorithms have shown considerable promise for the detection and classification of therapeutic plants. Natural chemicals found in medicinal plants are a great source for the creation of novel medications and treatments.However, because there are so many diverse species with comparable physical characteristics, it can be difficult to identify and characterize therapeutic plants. Additionally, the habitat, climate, and growing circumstances all have an impact on the chemical makeup of medicinal plants. Therefore, for medicinal plants to be used effectively in medicine, correct identification and classification are essential.
Description: Enrollment No. 191202
URI: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9976
Appears in Collections:B.Tech. Project Reports

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