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 Conference Papers 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/. Title A name given to the resource Handwritten Character Recognition of MODI Script using Convolutional Neural Network Based Feature Extraction Method and Support Vector Machine Classifier Subject The topic of the resource Autoencoder; Convolutional Neural Network; Feature Extraction; Handwritten Character Recognition; MODI Script; Pattern Recognition; Support Vector Machine Description An account of the resource Deep learning based algorithms are used in various pattern recognition tasks, including character recognition. Convolutional Neural Network (CNN) is effectively implemented for character recognition and is one of the best performing deep learning models. CNN can be used for character recognition directly or it can be used for extracting features in the character recognition process. Implementation of a feature extraction method using CNN autoencoder for MODI script character recognition is discussed in the paper. The extracted features are then subjected to Support Vector Machine (SVM) for the purpose of classification. The On-the-fly data augmentation method is used to add variability and generalization of the data set. MODI Script is an ancient Indian script and was used for writing Marathi until 1950. Various libraries and temples in India and abroad have a large collection of MODI documents. Character recognition related research of MODI script is still in infancy and research and development is necessary to extract the information from MODI manuscripts stored in various libraries. The performance of the proposed method, which uses CNN autoencoder as a feature extractor and an SVM based classifier gives very high accuracy and is better compared to the most accurate MODI character recognition method reported so far. 2020 IEEE. Creator An entity primarily responsible for making the resource Joseph S.; George J. Source A related resource from which the described resource is derived 2020 IEEE 5th International Conference on Signal and Image Processing, ICSIP 2020, pp. 32-36. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICSIP49896.2020.9339435" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICSIP49896.2020.9339435</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101127729&amp;doi=10.1109%2FICSIP49896.2020.9339435&amp;partnerID=40&amp;md5=d04cb5e3d98caffdb90f88c34d40ed07" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101127729&amp;doi=10.1109%2fICSIP49896.2020.9339435&amp;partnerID=40&amp;md5=d04cb5e3d98caffdb90f88c34d40ed07</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-172816896-8 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Joseph S., Christ (Deemed to Be University), Dept. of Computer Science, Bangalore, India, Carmel College for Women, Goa, India; George J., Christ (Deemed to Be University), Dept. of Computer Science, Bangalore, India