Plant Disease Detection Application Using Deep Learning (PLANTSCARE)

Plant Disease Detection

Authors

  • Mohammed Fuad Mohammed Ahmed Saif UTHM-FSKTM
  • Nureize Arbaiy

Keywords:

Plant disease, convolutional neural network, deep learning

Abstract

: Plant leaf diseases are conditions that harm a plant's leaves. One of the main problems that every farmer encounters is the diagnosis of plant diseases, which can be brought on by a variety of causes. The development of advanced computing technology has allowed for the improvement of agricultural decision-making. Deep learning technology is then useful in this circumstance. because it outperforms earlier conventional approaches in terms of dependability, accuracy, speed, and cost-effectiveness. As a result, the goal of this project is to develop an Android application that will allow farmers to identify the presence of plant diseases by taking a photo of the plant and using deep learning. This project will use the deep learning technique of convolutional neural networks (CNN). The model has been trained by Google Teachable machine platform on a dataset of images of diseased and healthy plants and is able to accurately identify various plant diseases. Without assistance from agronomists, the algorithm will provide correct answers about the type of plant disease. The prototyping model has been employed to assist the development of the web application system. The use of this application could improve crop productivity and contribute to the overall development of a country's agriculture industry.

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Published

30-11-2023

Issue

Section

Articles

How to Cite

Mohammed Fuad Mohammed Ahmed Saif, & Nureize Arbaiy. (2023). Plant Disease Detection Application Using Deep Learning (PLANTSCARE): Plant Disease Detection . Applied Information Technology And Computer Science, 4(2), 1091-1109. https://publisher.uthm.edu.my/periodicals/index.php/aitcs/article/view/11936