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Study of Different Control Strategies Applied to a Second-Order Nonlinear Tank Process Read chapter Read first chapter

2023 | OriginalPaper | Chapter

Plant Health Analyzer Using Convolutional Neural Networks

Authors : M. Bhavani, K. P. Peeyush, R. Jayabarathi

Published in: Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems

Publisher: Springer Nature Singapore

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Abstract

Plant diseases could lead to huge production loss for the cultivators. These diseases are typically in the form of visible symptoms like color changes on the surface of the leaves, different colored spots, or streaks. This region of interest is extracted using image processing, and the area of the disease-affected part of the leaf is calculated. This system is proposed to support agriculturists to identify plant diseases efficiently and constantly monitor the health conditions of the plants. A convolutional neural network is used to identify common diseases of a few types of fruit leaves. The overall accuracy of this system is found to be 90% with a loss of 2.8%. Determining the disease and the leaf’s disease-affected area will help in maintaining a better quality of the crop by taking the required actions.

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Metadata
Title
Plant Health Analyzer Using Convolutional Neural Networks
Authors
M. Bhavani
K. P. Peeyush
R. Jayabarathi
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems

Print ISBN: 978-981-19-7752-7

Electronic ISBN: 978-981-19-7753-4

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-19-7753-4_26