Article: Multi-class classification using convolution neural networks for plant leaf recognition of Ayurvedic plants Journal: International Journal of Computational Science and Engineering (IJCSE) 2022 Vol.25 No.1 pp.11 - 21 Abstract: Ayurveda is the traditional medicine system of India. The ingredients from which Ayurvedic medicines are made are mostly herbal and mineral in nature. Also, there are many herbal home remedies in India for general ailments. This knowledge has been passed down from generation to generation in large joint families. This knowledge is slowly fading away in the current generation of nuclear families. The current generation is unable to identify even locally available plants. The authors have come up with the idea of using convolution neural networks for solving this problem. In this solution, the images of leaves are used to identify the plant. This problem is a case of multi-class classification. A leaf image database is created and a neural network model is built using convolutional neural network (CNN). Keras deep learning framework with tensorflow as backend, is used for this purpose. The work presented in this paper is a part of larger research work in this area. This paper explains the developed CNN model and presents the results corresponding to six Ayurvedic leaves commonly available in and around the City of Visakhapatnam in the State of Andhra Pradesh. Inderscience Publishers - linking academia, business and industry through research

Title: Multi-class classification using convolution neural networks for plant leaf recognition of Ayurvedic plants

Authors: K.V.N. Rajesh; D. Lalitha Bhaskari

Addresses: Department of Computer Science and Systems Engineering, Andhra University College of Engineering (Autonomous), Andhra University, Visakhapatnam-530003, India ' Department of Computer Science and Systems Engineering, Andhra University College of Engineering (Autonomous), Andhra University, Visakhapatnam-530003, India

Abstract: Ayurveda is the traditional medicine system of India. The ingredients from which Ayurvedic medicines are made are mostly herbal and mineral in nature. Also, there are many herbal home remedies in India for general ailments. This knowledge has been passed down from generation to generation in large joint families. This knowledge is slowly fading away in the current generation of nuclear families. The current generation is unable to identify even locally available plants. The authors have come up with the idea of using convolution neural networks for solving this problem. In this solution, the images of leaves are used to identify the plant. This problem is a case of multi-class classification. A leaf image database is created and a neural network model is built using convolutional neural network (CNN). Keras deep learning framework with tensorflow as backend, is used for this purpose. The work presented in this paper is a part of larger research work in this area. This paper explains the developed CNN model and presents the results corresponding to six Ayurvedic leaves commonly available in and around the City of Visakhapatnam in the State of Andhra Pradesh.

Keywords: convolution neural networks; CNNs; multi-class classification; plant leaf recognition; PLR; leaf feature extraction.

DOI: 10.1504/IJCSE.2022.120790

International Journal of Computational Science and Engineering, 2022 Vol.25 No.1, pp.11 - 21

Received: 11 May 2020
Accepted: 29 Mar 2021
Published online: 08 Feb 2022 *

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Title: Multi-class classification using convolution neural networks for plant leaf recognition of Ayurvedic plants

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