Image-based disease detection and classification in Indian apple plant species by using deep learning

Wani, Sidrah Fayaz and Ashraf, Arselan and Sophian, Ali (2022) Image-based disease detection and classification in Indian apple plant species by using deep learning. Applied Research and Smart Technology (ARSTech), 3 (1). pp. 38-48. ISSN 2722-9637 E-ISSN 2722-9645

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Abstract

Plant diseases pose a significant danger to global food security, yet their timely diagnosis remains difficult across many regions of the world due to the lack of infrastructure. Traditional farming methods are insufficient to address the impending global food crises. As a result, agricultural product growth is critical, and new techniques and methods are required for efficient and sustainable farming practices that balance the supply chain according to customer demand. Even though India is one of the most agriculturally dependent countries, it nevertheless suffers from various agricultural shortages. Plant diseases that go unnoticed and untreated are one such deprivation. Developing a smart technique for plant disease detection is explored in this research. For this, we used deep learning to develop an intelligent system for image-based disease detection in Indian apple plant species. Specifically, this model uses a convolution neural network to identify diseases in apple plants. On the basis of 70% - 30% and 80 % - 20% dataset partition, the proposed model obtained an accuracy of 97.5 % and 98.4 %, respectively. The results obtained from this study illustrate the productive exploration along with the utility of the proposed model for future research by implementing various deep learning models and incorporating additional modules that will provide cure and preventative measures for the detected diseases.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Convolutional neural networks, Deep learning, Plant disease detection, Smart agriculture
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechatronics Engineering Kulliyyah of Engineering
Depositing User:	Dr Ali Sophian
Date Deposited:	03 Jan 2023 08:48
Last Modified:	03 Jan 2023 08:48
URI:	http://irep.iium.edu.my/id/eprint/102445

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