MEDICINAL PLANT IDENTIFICATION USING CNN

Abstract: —Accurate identification of medicinal plants is essential for ensuring the efficacy and safety of herbal treatments, particularly in regions where traditional medicine plays a vital role in primary healthcare. This study presents a deep learning-based approach for the automatic identification of medicinal plant species using Convolutional Neural Networks (CNNs). The proposed system has the potential to assist botanists, pharmacists, and traditional medicine practitioners in reliable and efficient plant identification, thereby reducing the risks associated with misidentification and promoting the sustainable use of medicinal flora. Future work includes expanding the dataset, incorporating image data from various environmental conditions, and developing a mobile application for real-time field use. Key Words: — Medicinal Plants, Leaf, CNN, Identification, artificial intelligence, Deep learning (ML)

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-05-14
DOI
https://doi.org/10.55041/ijsrem.spejss014
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
0.00
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article

MEDICINAL PLANT IDENTIFICATION USING CNN

Selifanov A.V., D. M.
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Spectroscopy and Chemometric Analyses
article

MEDICINAL PLANT IDENTIFICATION USING CNN

Selifanov A.V., D. M.
article en

Abstract

Abstract: —Accurate identification of medicinal plants is essential for ensuring the efficacy and safety of herbal treatments, particularly in regions where traditional medicine plays a vital role in primary healthcare. This study presents a deep learning-based approach for the automatic identification of medicinal plant species using Convolutional Neural Networks (CNNs). The proposed system has the potential to assist botanists, pharmacists, and traditional medicine practitioners in reliable and efficient plant identification, thereby reducing the risks associated with misidentification and promoting the sustainable use of medicinal flora. Future work includes expanding the dataset, incorporating image data from various environmental conditions, and developing a mobile application for real-time field use. Key Words: — Medicinal Plants, Leaf, CNN, Identification, artificial intelligence, Deep learning (ML)

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(05)
Openalex Percentile: Top 89%
Spectroscopy and Chemometric Analyses
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