Bulletin of Electrical Engineering and Informatics
Vol 11, No 5: October 2022

Design a mobile application to detect tomato plant diseases based on deep learning

Marwa Abdulla (University of Basrah)
Ali Marhoon (University of Basrah)



Article Info

Publish Date
01 Oct 2022

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.

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Journal Info

Abbrev

EEI

Publisher

Subject

Electrical & Electronics Engineering

Description

Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the ...