Resnet - Based Detection of Eggplant Leaf Diseases: A Machine Learning Approach
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Science and Information Technology | Philippines | Volume 14 Issue 2, February 2025 | Popularity: 5.3 / 10


     

Resnet - Based Detection of Eggplant Leaf Diseases: A Machine Learning Approach

Dr. John C. Amar


Abstract: This study focuses on developing an eggplant leaf disease detection system using the ResNet algorithm. The system utilizes machine learning to analyze and classify leaf diseases based on image data, ensuring accurate and efficient disease identification. The study follows a developmental research approach, assessing system performance based on ISO 25010 characteristics, including functional suitability, reliability, and usability. Results indicate that participants strongly agree with the system?s effectiveness, with high reliability and efficiency. The findings suggest that this detection system can serve as a valuable tool for farmers and agricultural professionals in disease management.


Keywords: ResNet, eggplant leaf disease, deep learning, convolutional neural network, CNN, agricultural technology


Edition: Volume 14 Issue 2, February 2025


Pages: 1684 - 1687


DOI: https://www.doi.org/10.21275/SR25226134757


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Dr. John C. Amar, "Resnet - Based Detection of Eggplant Leaf Diseases: A Machine Learning Approach", International Journal of Science and Research (IJSR), Volume 14 Issue 2, February 2025, pp. 1684-1687, https://www.ijsr.net/getabstract.php?paperid=SR25226134757, DOI: https://www.doi.org/10.21275/SR25226134757

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