Identification of medicinal plants using Deep Learning Techniques

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Singam Navya Sri; Akula Chandradeep; GANJI VENKATA MURALI KRISHNA; Gudivada Syalini Naga Chandra; MS DUDIKI SIRISHA

Identification of medicinal plants using Deep Learning Techniques

Authors: Singam Navya Sri, Akula Chandradeep, GANJI VENKATA MURALI KRISHNA, Gudivada Syalini Naga Chandra, MS DUDIKI SIRISHA

Unique Paper ID: 174240
Volume: 11
Issue: 10
PageNo: 4102-4108

Keywords: No Keywords Found

Abstract:
The identification of medicinal plants plays a critical role in various fields, including pharmaceuticals, traditional medicine, and biodiversity conservation. However, traditional methods of identifying these plants can be time-consuming, labor-intensive, and require expert knowledge. This project aims to leverage deep learning techniques to automate the identification of medicinal plants, thus providing an efficient and accurate solution. The study employs Convolutional Neural Networks (CNN), MobileNet, and a hybrid model combining MobileNet with Recurrent Neural Networks (RNN) to classify and identify different medicinal plants. The models are trained and validated using a comprehensive dataset of medicinal plant images, ensuring robust performance. This approach not only enhances identification accuracy but also reduces the dependency on expert botanists, making it accessible to a broader audience. Keywords: Medical plants, Deep learning, Convolutional Neural Networks (CNN) MobileNet Recurrent Neural Networks (RNN), Plant Identification, Image Classification.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 10
PageNo: 4102-4108

Identification of medicinal plants using Deep Learning Techniques

Available:https://ijirt.org/article?manuscript=174240

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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