Plant Disease Prediction Using Deep Learning

J. Jyotsna, Prachi Ramteke, Prity Baxla
International Journal of Computational and Electronic Aspects in Engineering
Volume 3: Issue 2, June 2022, pp 32-38

Author's Information
J. Jyotsna1 
Corresponding Author
1Department of Computer Science Engineering, Christian College of Engineering and Technology, Bhilai, India
jyotsnaj136@gmail.com

Prachi Ramteke2
2Department of Computer Science Engineering, Christian College of Engineering and Technology, Bhilai, India

 Prity Baxla3
3Department of Computer Science Engineering, Christian College of Engineering and Technology, Bhilai, India
Technical Article -- Peer Reviewed
First online on – 08 August 2022

Open Access article under Creative Commons License

Cite this article –J. Jyotsna, Prachi Ramteke, Prity Baxla “Plant Disease Prediction Using Deep Learning”, International Journal of Computational and Electronic Aspects in Engineering, RAME Publishers, vol. 3, Issue 2, pp. 32-38, 2022.
https://doi.org/10.26706/ijceae.3.2.arset1002

Abstract:-
This study aims to develop an android application to detect and identify plant diseases through deep convolutional neural network. Plant disease is a critical issue in agricultural countries like Bangladesh. Every year production of crops sustains heavy loss due to diseases. It is quite difficult to detect plant diseases with human eyes. So it is essential to build an automated system to detect the diseases. The proposed disease detection model takes an image of a plant leaf as input, processes it and uses deep convolutional neural network to detect and identify the disease. The developed mobile application is user-friendly and can be used by farmers without much technical knowledge.
Index Terms:-
Deep Convolutional Neural Network, Image Processing, Android Application, Plant Disease Detection.
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