Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Deep Learning for Early Detection of Tomato Leaf Diseases: A ResNet-18 Approach for Sustainable Agriculture Subject The topic of the resource binary classification; Convolution neural networks; deep learning; disease detection; tomato crop health Description An account of the resource The paper explores the application of Convolutional Neural Networks (CNNs), specifically ResNet-18, in revolutionizing the identification of diseases in tomato crops. Facing threats from pathogens like Phytophthora infestans, timely disease detection is crucial for mitigating economic losses and ensuring food security. Traditionally, manual inspection and labour-intensive tests posed limitations, prompting a shift to CNNs for more efficient solutions. The study uses a well-organized dataset, employing data preprocessing techniques and ResNet-18 architecture. The model achieves remarkable results, with a 91% F1 score, indicating its proficiency in distinguishing healthy and unhealthy tomato leaves. Metrics such as accuracy, sensitivity, specificity, and a high AUC score on the ROC curve underscore the model's exceptional performance. The significance of this work lies in its practical applications for early disease detection in agriculture. The ResNet-18 model, with its high precision and specificity, presents a powerful tool for crop management, contributing to sustainable agriculture and global food security. (2024), (Science and Information Organization). All Rights Reserved. Creator An entity primarily responsible for making the resource Asha M.S.; Yogish H.K. Source A related resource from which the described resource is derived International Journal of Advanced Computer Science and Applications, Vol-15, No. 1, pp. 876-883. Publisher An entity responsible for making the resource available Science and Information Organization Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.14569/IJACSA.2024.0150188" target="_blank" rel="noreferrer noopener">https://doi.org/10.14569/IJACSA.2024.0150188</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185005271&amp;doi=10.14569%2FIJACSA.2024.0150188&amp;partnerID=40&amp;md5=2332fbaba90cd4dd808c8071e7d87e36" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185005271&amp;doi=10.14569%2fIJACSA.2024.0150188&amp;partnerID=40&amp;md5=2332fbaba90cd4dd808c8071e7d87e36</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 2158107X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Asha M.S., Department of Computer Science and Engineering, Christ University (Deemed to be University), Karnataka, India; Yogish H.K., Department of Information Science and Engineering, M S Ramaiah Institute of Technology, Karnataka, India, Visvesvaraya Technological University, Belagavi, 590018, India