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Call for Papers:Vol.11 Issue.3

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Title: :  A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS
PaperId: :  21624
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 5 2023
DUI:    16.0415/IJARIIE-21624
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Athul E BKKMMPTC MALA
Abhinav M RKKMMPTC MALA
Amal E BKKMMPTC MALA
Ashwin VenugopalKKMMPTC MALA
Basil KuriakoseKKMMPTC MALA
Jeffin JoshyKKMMPTC MALA
Ajith P JKKMMPTC MALA
Bindu AntoKKMMPTC MALA

Abstract

Computer Engineering
Medicinal plants, real-time web application, deep learning, CNN- Convolutional Neural Network, Image recognition, Botanical classification
Medicinal plants have been a source of healing and wellness for centuries, yet many people today lack awareness of these valuable natural resources and their potential uses. Identifying medicinal plants can be a challenging and time-consuming task, often requiring expert knowledge. Our web application transcends mere identification; it serves as an inclusive platform, not only revealing the plants' identities but also shedding light on their historical, cultural, and contemporary applications. In this project, we introduce a novel approach to address this issue by developing a real-time web application powered by deep learning. real-time web application leverages the capabilities of deep learning to provide instantaneous and accurate results for various tasks, from image recognition to data analysis. Powered by advanced neural networks, it offers users a seamless and efficient experience, making complex tasks feel effortless. Our system is designed to identify medicinal plants and provide information about their uses in real-time. To tackle this challenge, we introduce a pioneering solution: specifically, Convolutional Neural Networks (CNN) in image recognition and data analysis. The purpose of this web application is to make valuable information about medicinal plants more accessible to the general public. Beyond mere identification, our web application goes a step further by offering insightful awareness of usage. For each recognized plant, users receive detailed information about its botanical classification, medicinal properties, historical uses, preparation methods, and potential side effects or precautions. This comprehensive knowledge empowers individuals to make informed decisions about the utilization of medicinal plants for various health and wellness purposes. This project aims to bridge the knowledge gap surrounding medicinal plants, making this valuable information more accessible to the general public.

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IJARIIE Athul E B, Abhinav M R, Amal E B, Ashwin Venugopal, Basil Kuriakose, Jeffin Joshy, Ajith P J, and Bindu Anto. "A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 5 2023 Page 500-505
MLA Athul E B, Abhinav M R, Amal E B, Ashwin Venugopal, Basil Kuriakose, Jeffin Joshy, Ajith P J, and Bindu Anto. "A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS." International Journal Of Advance Research And Innovative Ideas In Education 9.5(2023) : 500-505.
APA Athul E B, Abhinav M R, Amal E B, Ashwin Venugopal, Basil Kuriakose, Jeffin Joshy, Ajith P J, & Bindu Anto. (2023). A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS. International Journal Of Advance Research And Innovative Ideas In Education, 9(5), 500-505.
Chicago Athul E B, Abhinav M R, Amal E B, Ashwin Venugopal, Basil Kuriakose, Jeffin Joshy, Ajith P J, and Bindu Anto. "A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 5 (2023) : 500-505.
Oxford Athul E B, Abhinav M R, Amal E B, Ashwin Venugopal, Basil Kuriakose, Jeffin Joshy, Ajith P J, and Bindu Anto. 'A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, 2023, p. 500-505. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/A_DEEP_LEARNING_BASED_REAL_TIME_WEB_APPLICATION_FOR_MEDICINAL_PLANT_IDENTIFICATION_AND_USAGE_AWARENESS_ijariie21624.pdf (Accessed : ).
Harvard Athul E B, Abhinav M R, Amal E B, Ashwin Venugopal, Basil Kuriakose, Jeffin Joshy, Ajith P J, and Bindu Anto. (2023) 'A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS', International Journal Of Advance Research And Innovative Ideas In Education, 9(5), pp. 500-505IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/A_DEEP_LEARNING_BASED_REAL_TIME_WEB_APPLICATION_FOR_MEDICINAL_PLANT_IDENTIFICATION_AND_USAGE_AWARENESS_ijariie21624.pdf (Accessed : )
IEEE Athul E B, Abhinav M R, Amal E B, Ashwin Venugopal, Basil Kuriakose, Jeffin Joshy, Ajith P J, and Bindu Anto, "A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, pp. 500-505, Sep-Oct 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/A_DEEP_LEARNING_BASED_REAL_TIME_WEB_APPLICATION_FOR_MEDICINAL_PLANT_IDENTIFICATION_AND_USAGE_AWARENESS_ijariie21624.pdf [Accessed : ].
Turabian Athul E B, Abhinav M R, Amal E B, Ashwin Venugopal, Basil Kuriakose, Jeffin Joshy, Ajith P J, and Bindu Anto. "A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 5 ().
Vancouver Athul E B, Abhinav M R, Amal E B, Ashwin Venugopal, Basil Kuriakose, Jeffin Joshy, Ajith P J, and Bindu Anto. A DEEP LEARNING-BASED REAL-TIME WEB APPLICATION FOR MEDICINAL PLANT IDENTIFICATION AND USAGE AWARENESS. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(5) : 500-505. Available from: https://ijariie.com/AdminUploadPdf/A_DEEP_LEARNING_BASED_REAL_TIME_WEB_APPLICATION_FOR_MEDICINAL_PLANT_IDENTIFICATION_AND_USAGE_AWARENESS_ijariie21624.pdf
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