Identification of An Ayurvedic Leaf Using Convolutional Neural Network

Authors: Ravina Kolekar, Priyanka Ahire, Anushka Dholi, Prof. Kanchan Dhomse

Country: India

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Abstract: Medicinal plants play a crucial role in traditional medicine and drug discovery due to their diverse chemical compositions and therapeutic properties. However, the accurate identification of medicinal plant species based on their leaves remains a challenging task. This paper presents a comprehensive review of recent advances in the application of machine learning techniques for medicinal leaf identification.
The review begins with an overview of traditional methods used for medicinal leaf identification, highlighting their limitations and the need for automated, efficient, and accurate identification methods. It then discusses the various machine learning approaches, including deep learning, convolutional neural networks (CNNs), support vector machines (SVMs), and random forests, that have been applied to medicinal leaf identification.
The review also discusses the challenges and future directions in the field, such as the need for large and diverse datasets, robust feature extraction techniques, and the integration of multi-modal data sources for improved identification accuracy. Overall, this review provides insights into the current state-of-the-art in medicinal leaf identification using machine learning and highlights potential avenues for future research.

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Paper Id: 230581

Published On: 2024-04-17

Published In: Volume 12, Issue 2, March-April 2024

Cite This: Identification of An Ayurvedic Leaf Using Convolutional Neural Network - Ravina Kolekar, Priyanka Ahire, Anushka Dholi, Prof. Kanchan Dhomse - IJIRMPS Volume 12, Issue 2, March-April 2024.

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