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.
Authors
- Mohammed M. Abu Shquier
- Nesrine Atitallah (ORCID: https://orcid.org/0000-0002-5992-174X)
- Khaled M. Alhawiti (ORCID: https://orcid.org/0009-0005-4529-1301)
- Khalid M.O. Nahar (ORCID: https://orcid.org/0000-0002-3846-7912)
- Dalal Z. Zreiqat
Institutions
- Arab Open University (SA)
- Jerash University (JO)
- University of Tabuk (SA)
- Yarmouk University (JO)
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