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 Poorani, S.; Singh, Komal; Priya Stella Mary, I.; Brinda, P.; Srimathi, S.; Jegajothi, B. Title A name given to the resource Robust Rice Leaf Disease Detection using Advanced Preprocessing and Deep CNNs for Class Imbalance Resolution 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 International Conference on Intelligent Systems and Computational Networks, ICISCN 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICISCN64258.2025.10934702" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICISCN64258.2025.10934702</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105002680513?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105002680513?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 Poorani S., Kongu Engineering College, Department of Computer Technology, Perundurai, Erode, India; Singh K., Babasaheb Bhimrao Ambedkar University, Lucknow, India; Priya Stella Mary I., Christ University, Department of Computer Science, Yeshwanthpur Campus, Bangalore, India; Brinda P., Veltech Hightech Dr. Rangarajan Dr. Sakunthala Engineering College, Department of Computer Science and Engineering, Avadi, Chennai, India; Srimathi S., Saveetha School of Engineering, Simats, Department of Bio Technology, Chennai, India; Jegajothi B., Srs Tech Solutions, Chennai, India Description An account of the resource This study addresses the growing challenges posed by plant diseases, particularly in the rice industry, which is vital for many communities. The research propose a robust framework that integrates Deep Convolutional Neural Networks (Deep CNN) with advanced preprocessing techniques to identify rice leaf diseases, including Brown Spot, Leaf Blast, Hispa, and healthy leaves. Our approach employs normalization to enhance convergence during training and data augmentation to improve model generalizability. Additionally, implement the Synthetic Minority Over-sampling Technique (SMOTE) to create synthetic samples for under-represented classes, addressing class imbalance within the dataset. Experimental results demonstrate the model's impressive accuracy, achieving 98.2% for Brown Spot, 97.5% for Leaf Blast, 94.3% for Hispa, and 96.8% for healthy leaves. Furthermore, our method outperforms established CNN architectures such as AlexNet, VGG16, and ResNet50, showcasing the effectiveness of sophisticated preprocessing in enhancing plant disease detection systems and supporting food security initiatives. 2025 IEEE. Subject The topic of the resource advanced preprocessing techniques; class imbalance resolution; data augmentation; deep convolutional neural network (deep CNN); rice leaf disease detection; synthetic minority over-sampling technique (SMOTE) Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152924-6; 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