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 Faculty Publications Conference Paper Faculty Publications- Conference Papers 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/. Creator An entity primarily responsible for making the resource Kumar, Prince; Anuj; Ragavendra, T.S.; Chinnaiyan, R.; Sabarmathi, G.; Khanna, Vimal Kumar Title A name given to the resource Early Detection and Analysis of Potato Leaf Diseases Using Deep Learning based CNN Models Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 2nd International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICCAMS65118.2025.11234494" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCAMS65118.2025.11234494</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105030062478?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105030062478?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kumar P., Lingaya's Vidyapeeth, AI/ML Lab, Centre of Excellence, Department of Computer Science and Engineering, Haryana, Faridabad, India; Anuj, Lingaya's Vidyapeeth, AI/ML Lab, Centre of Excellence, Department of Computer Science and Engineering, Haryana, Faridabad, India; Ragavendra T.S., S-Vyasa School of Advanced Studies, Department of Computer Science and Engineering, Bengaluru, India; Chinnaiyan R., Lingaya's Vidyapeeth, AI/ML Lab, Centre of Excellence, Department of Computer Science and Engineering, Haryana, Faridabad, India; Sabarmathi G., Christ University, School of Computer Science, Bangalore, India; Khanna V.K., Lingaya's Vidyapeeth, AI/ML Lab, Centre of Excellence, Department of Computer Science and Engineering, Haryana, Faridabad, India Description An account of the resource Potato diseases pose a significant threat to global agricultural productivity, leading to severe economic losses. Early and accurate disease detection is crucial for effective disease management and improved crop yield. This research explores deep learning techniques for automated potato disease prediction using convolutional neural networks (CNNs). A large dataset of potato leaf images is used to train and validate the model, ensuring robustness and accuracy. The proposed deep learning model efficiently classifies common potato diseases, such as late blight and early blight, with high precision. Performance evaluation metrics, include accuracy, The integration of deep learning in disease prediction minimizes the reliance on manual inspection, providing farmers with a cost-effective and scalable solution. Additionally, we analyze the impact of transfer learning and data augmentation on model performance. The results highlight the potential of AI-driven approaches in precision agriculture, offering real-time disease diagnosis and early intervention strategies. This research contributes to the advancement of smart farming technologies, ensuring sustainable crop protection and food security. Future work will focus on optimizing the model for real-world deployment through mobile applications and IoT-based systems. 2025 IEEE. Subject The topic of the resource Accuracy; Convolutional Neural Networks (CNNs); Deep learning; Early blight; Late blight Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833159610-1; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online