Smart Agriculture for Beans: AI-Driven Disease Identification and Classification

Introduce deep learning methods for automatic detection in this paper of plant disease using YOLOv8. The algorithm was developed using a unique dataset that included pictures of beans. also applied segmentation for the leaf to improve the localization of disease, the incorporated leaf segmentation techniques using color-based thresholding and morphological operations, which help isolate the affected regions from complex backgrounds. compared the results with previous work that depended on models like EfficientNet. The results show that the model achieved high accuracy and precision compared to previous work . The model reached an accuracy of 99.5%, Moreover the model provides real-time object detection and precise localization, making it suitable for practical agriculture applications more than the traditional ways.

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Publication Details

Journal
Multicriteria Algorithms with Applications
Published
2025-06-30
DOI
https://doi.org/10.61356/j.mawa.2025.7598
Primary Topic
Financial Literacy, Pension, Retirement Analysis
Type
article
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article

Smart Agriculture for Beans: AI-Driven Disease Identification and Classification

Multicriteria Algorithms with Applications
Financial Literacy, Pension, Retirement Analysis
article

Smart Agriculture for Beans: AI-Driven Disease Identification and Classification

article en

Abstract

Introduce deep learning methods for automatic detection in this paper of plant disease using YOLOv8. The algorithm was developed using a unique dataset that included pictures of beans. also applied segmentation for the leaf to improve the localization of disease, the incorporated leaf segmentation techniques using color-based thresholding and morphological operations, which help isolate the affected regions from complex backgrounds. compared the results with previous work that depended on models like EfficientNet. The results show that the model achieved high accuracy and precision compared to previous work . The model reached an accuracy of 99.5%, Moreover the model provides real-time object detection and precise localization, making it suitable for practical agriculture applications more than the traditional ways.

Multicriteria Algorithms with ApplicationsVol. 7
Zagazig University (EG), October 6 University (EG)
Zero hunger
Openalex Percentile: Top 35%
Financial Literacy, Pension, Retirement Analysis
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