A Hybrid Network for Indian Medical Plant Species Identification

T. Meeradevi, Saravanakumar P, Saran S

2025

Abstract

India is home to over 8,000 medicinal plant species, forming the foundation of traditional healthcare systems. Accurate identification of these plants is crucial for preserving traditional knowledge and advancing botany, pharmacology, and agriculture. This research introduces the Hybrid Attention Network for Indian Medicinal Plant Species Classification, a deep learning-based approach combining InceptionV3 and DenseNet121 with attention mechanisms to enhance classification accuracy. The dataset comprises approximately 18,000 images of 200 distinct plant species. The hybrid model leverages the pre-trained weights of InceptionV3 and DenseNet121 for feature extraction, combining their outputs through channel attention layers. These mechanisms focus on key image features, such as leaf patterns, enabling the model to differentiate species with subtle distinctions. The integration of attention mechanisms allows the model to retain only the most relevant information, achieving a deeper understanding of visual data. With an ambitious goal of surpassing 95% accuracy, the hybrid model demonstrates significant improvements, benefiting from hyperparameter optimization and fine-tuning. A key outcome of this research is a user-friendly mobile application that democratizes plant species identification. Users can upload or capture images of plants for instant and accurate classification, making the app an invaluable tool for botanists, farmers, healthcare practitioners, and enthusiasts.

Paper Citation

in Harvard Style

Meeradevi T., P S. and S S. (2025). A Hybrid Network for Indian Medical Plant Species Identification. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 476-484. DOI: 10.5220/0013622100004664

in Bibtex Style

@conference{incoft25,
author={T. Meeradevi and Saravanakumar P and Saran S},
title={A Hybrid Network for Indian Medical Plant Species Identification},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT},
year={2025},
pages={476-484},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013622100004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT
TI - A Hybrid Network for Indian Medical Plant Species Identification
SN - 978-989-758-763-4
AU - Meeradevi T.
AU - P S.
AU - S S.
PY - 2025
SP - 476
EP - 484
DO - 10.5220/0013622100004664
PB - SciTePress