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 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/. Creator An entity primarily responsible for making the resource Manimekala, B.; Umamaheswari, D.; Rozario, Juliet; Kannan, M.; Savitha, P. Margaret Title A name given to the resource Dysgraphia Disorder Detection and Classification Using Deep Learning Technique 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 SN Computer Science;Volume;6;Issue;3;Article No.;269; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s42979-025-03825-5" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42979-025-03825-5</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105000063828?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105000063828?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 Manimekala B., Department of Computer Science, School of Sciences, Christ University, Karnataka, Bangalore, India; Umamaheswari D., Department of Computer Science, School of Sciences, Christ University, Karnataka, Bangalore, India; Rozario J., Department of Computer Science, School of Sciences, Christ University, Karnataka, Bangalore, India; Kannan M., Department of Computer Science, School of Sciences, Christ University, Karnataka, Bangalore, India; Savitha P.M., Department of Computer Science, School of Sciences, Christ University, Karnataka, Bangalore, India Description An account of the resource Dysgraphia, a neurological condition, impedes childrens acquisition of standard writing abilities, leading to subpar written expression. Inadequate or underdeveloped writing proficiency can adversely affect a childs educational progress and self-esteem. To address this issue, our study involved compiling a novel dataset of handwritten operations and extracting an array of features to encapsulate the various dimensions of handwriting characteristics. This research presents the Rotational Region Convolutional Neural Network (R2CNN) as a novel approach to tackle this issue. The R2CNN framework integrates a multitask refinement network for accurate tilted box detection and a text region proposal network (Text RPN) to identify potential text areas. To address the imbalance in the training categories and mitigate the overpopulation problem through feature elimination, a balance parameter is incorporated into the loss function. This research focused on identifying dysgraphia by analyzing these extracted features, which included both handwriting and geometric elements. The feature-learning stage of deep transfer learning effectively extracts and applies characteristics to identify dysgraphia. Research findings indicate that this study can use handwritten images to detect dysgraphia in children. The results of the data-gathering process show that this investigation can leverage samples of handwritten text to recognize dysgraphia among young individuals. The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource Deep learning; Dysgraphia detection; Handwriting diagnosis; Rotating region CNN; Text-RPN Publisher An entity responsible for making the resource available Springer Relation A related resource ISSN: 2662995X; Language A language of the resource English Type The nature or genre of the resource Article 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