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2023 | OriginalPaper | Chapter

A Novel Approach to Detect Plant Disease Using DenseNet-121 Neural Network

Authors : Nilesh Dubey, Esha Bhagat, Swapnil Rana, Kirtan Pathak

Published in: Smart Trends in Computing and Communications

Publisher: Springer Nature Singapore

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Abstract

The disease of crops is a major risk to food security and can incur a makeable loss to the people. But, the latest development in deep learning for solving this problem surpasses all the traditional methods in terms of efficiency, time period for detection and accuracy. In this paper, we came up with a rapid identification of leaf image and classify the image to correct class by using classical deep neural network architecture, DenseNet-121. This deep learning model has the ability to recognize 15 types of different plant disease, three of which are healthy ones, for better accurate results. The algorithm is highly optimized to produce results in less than 5 s after being fed into the system. The model’s total testing accuracy for plant disease detection is 99%.

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Metadata
Title
A Novel Approach to Detect Plant Disease Using DenseNet-121 Neural Network
Authors
Nilesh Dubey
Esha Bhagat
Swapnil Rana
Kirtan Pathak
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Smart Trends in Computing and Communications

Print ISBN: 978-981-16-9966-5

Electronic ISBN: 978-981-16-9967-2

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-16-9967-2_7

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