Design a mobile application to detect tomato plant diseases based on deep learning
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Published:2022-10-01
Issue:5
Volume:11
Page:2629-2636
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ISSN:2302-9285
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Container-title:Bulletin of Electrical Engineering and Informatics
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language:
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Short-container-title:Bulletin EEI
Author:
Abdulla MarwaORCID,
Marhoon AliORCID
Abstract
Plant diseases consider the most dominant matter for farmers' concerns becausethe operation of discovering and dealing with them requires accuracy, experience, and time. Therefore, this paper proposes an approach to classify seven varieties of tomato diseases using deep learning models. A dataset of 10448 images from PlantVillage and google utilize to train the deep learning (CNN models). The trained models proved their ability to classify with high accuracy, as the highest testing accuracy reached 95.71% for the proposed model for 50 epochs only. The resulted best model is published to a mobile application using the android studioplatform, this application enables the farmer to classify plant diseases accurately and easily. The proposed model and mobile application could be extended to classify as many plant diseases as possible.
Publisher
Institute of Advanced Engineering and Science
Subject
Electrical and Electronic Engineering,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Instrumentation,Information Systems,Control and Systems Engineering,Computer Science (miscellaneous)
Cited by
1 articles.
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