Plantae: Medicinal Plant Classification Using Machine Learning

Registration ID: IJNRD_217320

Published ID: IJNRD2405137

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Vaidehi subhedar , Simran Bhisikar , Akansha Patil , Rutuja Hulke , Harshal Waghmare

Keywords: Convolutional neural networks, deep learning, and neural networks

Ayurveda has employed plants as a source of healing since the Vedic era. The most crucial manual process in the creation of ayurveda medicine is the identification of the proper plant. The automatic identification of these units is crucial due to the necessity for mass production. Our major goal is to develop a Deep Learning-based system for identifying medicinal plants. This approach will accurately classify the various types of medicinal plants. It is crucial to classify and identify medicinal plants in order to provide better care. We employ physiological or morphological leaf texture, shape, and color as the characteristics set of the data. To build a highly accurate system, we use CNN architecture to train our data.

Published Paper   E-Certificate

Vaidehi subhedar, Simran Bhisikar, Akansha Patil, Rutuja Hulke, & Harshal Waghmare (May-2024). Plantae: Medicinal Plant Classification Using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), b239-b245. https://ijnrd.org/papers/IJNRD2405137.pdf

Volume 9 Issue 5, May-2024

Pages : b239-b245

Paper Reg. ID: IJNRD_217320

Published Paper Id: IJNRD2405137

Downloads: 000121983

Research Area: Health Science 

Country: nagpur, maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405137.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405137

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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