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Cognitive Computing and Cyber Physical Systems. 4th EAI International Conference, IC4S 2023, Bhimavaram, Andhra Pradesh, India, August 4-6, 2023, Proceedings, Part I

Research Article

Medical Plants Identification Using Leaves Based on Convolutional Neural Networks

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-48888-7_14,
        author={B Ch S N L S Sai Baba and Mudhindi Swathi and Kompella Bhargava Kiran and B. R. Bharathi and Venkata Durgarao Matta and CH. Lakshmi Veenadhari},
        title={Medical Plants Identification Using Leaves Based on Convolutional Neural Networks},
        proceedings={Cognitive Computing and Cyber Physical Systems. 4th EAI International Conference, IC4S 2023, Bhimavaram, Andhra Pradesh, India, August 4-6, 2023, Proceedings, Part I},
        proceedings_a={IC4S},
        year={2024},
        month={1},
        keywords={Image Processing CNN Medical Plants Computer Vision},
        doi={10.1007/978-3-031-48888-7_14}
    }
    
  • B Ch S N L S Sai Baba
    Mudhindi Swathi
    Kompella Bhargava Kiran
    B. R. Bharathi
    Venkata Durgarao Matta
    CH. Lakshmi Veenadhari
    Year: 2024
    Medical Plants Identification Using Leaves Based on Convolutional Neural Networks
    IC4S
    Springer
    DOI: 10.1007/978-3-031-48888-7_14
B Ch S N L S Sai Baba1,*, Mudhindi Swathi1, Kompella Bhargava Kiran1, B. R. Bharathi1, Venkata Durgarao Matta1, CH. Lakshmi Veenadhari1
  • 1: Computer Science and Engineering Department, Vishnu Institute of Technology
*Contact email: sai.ossr524@gmail.com

Abstract

The ayurvedic medicines have played a crucial role in health system, only a few experts could identify the herbs and know the ayurvedic properties of these herbs. These medicines prepared from the herbs having less side effects as compared to other general medicines. Most of the patients and general medicine users with different diseases are not unaware of the existence of herbal plants and their medical uses and benefits. To make ease of identifying the plants and its medical properties based on the leaf structure, authors developed a system having three architectures which works with Convolutional Neural Networks. Resnet-18, Resnet-50, MobileNet-V2 architectures were used in freeze and unfreeze layers settings. Authors considered ten different kinds of herbal leaves for implementation of the system, in which two thirds of the data used for training and one third for testing. The overall performance of this architecture is checked using accuracy measure and it is observed that three models with freeze layers were showing good performance. Out of these three architectures, Resnet-50 shown accuracy of 95.33%.

Keywords
Image Processing CNN Medical Plants Computer Vision
Published
2024-01-05
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-48888-7_14
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