Medicinal Plant Recognition Based on the Seedling Image and Deep Learning

In the realm of botanical science and environmental conservation, identifying medicinal plant species accurately and efficiently is crucial for their sustainable cultivation and conservation. This paper introduces a novel approach that leverages seedling images and deep learning techniques to develop a computer vision system. The system aims to recognize medicinal plants at their early growth stages, a task that is fundamental for effective plant management and preservation efforts. The proposed work utilizes the Inception 3, a deep convolutional neural network (CNN) architecture, trained on a comprehensive dataset of seedling images from diverse medicinal plant species. Evaluating the system's performance with various metrics reveals its exceptional accuracy, reaching up to 97.6% in identifying medicinal plant species. This model holds promise for applications in plant conservation, biodiversity assessment, and the cultivation of medicinal plants.

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Publication Details

Journal
Journal of Advanced Research in Applied Sciences and Engineering Technology
Published
2024-10-09
DOI
https://doi.org/10.37934/araset.58.1.209219
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.60
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article

Medicinal Plant Recognition Based on the Seedling Image and Deep Learning

Mohammed M. Abu Shquier, Nesrine Atitallah, Khaled M. Alhawiti, Khalid M.O. Nahar et al.
1 citations
Journal of Advanced Research in Applied Sciences and Engineering Technology
Smart Agriculture and AI
0.60
article

Medicinal Plant Recognition Based on the Seedling Image and Deep Learning

Mohammed M. Abu Shquier, Nesrine Atitallah, Khaled M. Alhawiti, Khalid M.O. Nahar, Dalal Z. Zreiqat
article en
1 citations

Abstract

In the realm of botanical science and environmental conservation, identifying medicinal plant species accurately and efficiently is crucial for their sustainable cultivation and conservation. This paper introduces a novel approach that leverages seedling images and deep learning techniques to develop a computer vision system. The system aims to recognize medicinal plants at their early growth stages, a task that is fundamental for effective plant management and preservation efforts. The proposed work utilizes the Inception 3, a deep convolutional neural network (CNN) architecture, trained on a comprehensive dataset of seedling images from diverse medicinal plant species. Evaluating the system's performance with various metrics reveals its exceptional accuracy, reaching up to 97.6% in identifying medicinal plant species. This model holds promise for applications in plant conservation, biodiversity assessment, and the cultivation of medicinal plants.

Journal of Advanced Research in Applied Sciences and Engineering Technology
Arab Open University (SA), Jerash University (JO), University of Tabuk (SA), Yarmouk University (JO)
Openalex Percentile: Top 21%
Smart Agriculture and AI
0.60
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