INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Traditional methods of identifying medicinal herbs present significant challenges to various stakeholders involved in herbal medicine. Herb collectors often rely on experience and expertise passed down through generations, which can be subjective and inconsistent. Researchers face hurdles in accurately cataloging and studying medicinal plant species due to manual identification processes' laborious and time-consuming nature. Medicinal Plant Identification project merges state-of-the-art technology with age-old botanical wisdom to offer a holistic herb identification and usage recommendation solution. ResNet50 model was trained for the project and an intuitive web interface was developed using Flask, users can effortlessly upload images of medicinal plants and receive precise predictions.
Keywords:
ResNet50, medicinal plants, transfer learning, deep learning
Cite Article:
"Medicinal Plant Identification via ResNet50 Transfer Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 4, page no.1217 - 1221, April-2024, Available :http://www.ijsdr.org/papers/IJSDR2404176.pdf
Downloads:
000338172
Publication Details:
Published Paper ID: IJSDR2404176
Registration ID:210985
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 1217 - 1221
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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