{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:00:28Z","timestamp":1777705228863,"version":"3.51.4"},"reference-count":16,"publisher":"SAGE Publications","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,9,15]]},"abstract":"<jats:p>Classical Handwriting recognition systems depend on manual feature extraction with a lot of previous domain knowledge. It\u2019s difficult to train an optical character recognition system based on these requirements. Deep learning approaches are at the centre of handwriting recognition research, which has yielded breakthrough results in recent years. However, the rapid growth in the amount of handwritten data combined with the availability of enormous processing power necessitates an increase in recognition accuracy and warrants further investigation. Convolutional Neural Networks (CNNs) are extremely good at perceiving the structure of handwritten characters in ways that allow for the automatic extraction of distinct features, making CNN the best method for solving handwriting recognition problems. In this research work, a novel CNN has built to modify the network structure with Orthogonal Learning Chaotic Grey Wolf Optimization (CNN-OLCGWO). This modification is adopted for evolutionarily optimizing the number of hyper-parameters. This proposed optimizer predicts the optimal values from the fitness computation and shows better efficiency when compared to various other conventional approaches. The ultimate target of this work is to endeavour a suitable path towards digitalization by offering superior accuracy and better computation. Here, MATLAB 2018b has been used as the simulation environment to measure metrics like accuracy, recall, precision, and F-measure. The proposed CNN- OLCGWO offers a superior trade-off in contrary to prevailing approaches.<\/jats:p>","DOI":"10.3233\/jifs-211242","type":"journal-article","created":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T14:33:05Z","timestamp":1628605985000},"page":"3727-3737","source":"Crossref","is-referenced-by-count":35,"title":["An effective digit recognition model using enhanced convolutional neural network based chaotic grey wolf optimization"],"prefix":"10.1177","volume":"41","author":[{"given":"P.","family":"Preethi","sequence":"first","affiliation":[{"name":"Department of CSE, Kongunadu College of Engineering and Technology, Trichy, Tamil Nadu, India"}]},{"given":"R.","family":"Asokan","sequence":"additional","affiliation":[{"name":"Department of ECE, Kongunadu College of Engineering and Technology, Trichy, Tamil Nadu, India"}]},{"given":"N.","family":"Thillaiarasu","sequence":"additional","affiliation":[{"name":"School of Computing and Information Technology, REVA University, Bengaluru, India"}]},{"given":"T.","family":"Saravanan","sequence":"additional","affiliation":[{"name":"Department of CSE, Galgotias College of Engineering and Technology, Greater Noida, India"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-211242_ref1","first-page":"3304","article-title":"End-to-end text recognition with convolutional neural networks","volume":"1","author":"Wang","year":"2012","journal-title":"International Conference on Pattern Recognition"},{"issue":"11","key":"10.3233\/JIFS-211242_ref2","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Gradient based learning applied to document recognition","volume":"86","author":"LeCun","year":"2017","journal-title":"Proc IEEE"},{"key":"10.3233\/JIFS-211242_ref3","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/978-981-13-6783-0_3","article-title":"Character recognition from handwritten image using convolutional neural networks","volume":"922","author":"Jana","year":"2019","journal-title":"Recent Trends in Signal and Image Processing, Advances in Intelligent Systems and Computing"},{"key":"10.3233\/JIFS-211242_ref4","doi-asserted-by":"crossref","first-page":"27","DOI":"10.34257\/GJCSTDVOL19IS2PG27","article-title":"Recognition of handwritten digit using convolutional neural network (CNN)","volume":"19","author":"Hossain","year":"2019","journal-title":"Glob J Comput Sci Technol D Neural ArtifIntell"},{"key":"10.3233\/JIFS-211242_ref6","first-page":"142","article-title":"Handwriting recognition using deep learning","volume":"18","author":"Arora","year":"2018","journal-title":"International Conference on Advances in Computing, Communication Control and Networking (ICACCCN2018)"},{"issue":"6","key":"10.3233\/JIFS-211242_ref9","first-page":"6","article-title":"Handwritten script recognition using soft computing","volume":"1","author":"Pandey","year":"2012","journal-title":"International Journal of Advanced Computer Science Electronics Engineering"},{"issue":"3","key":"10.3233\/JIFS-211242_ref12","first-page":"31","article-title":"Artificial neural networks: a tutorial","volume":"29","author":"Jain","year":"2006","journal-title":"Computers and Electrical"},{"issue":"5","key":"10.3233\/JIFS-211242_ref13","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1016\/j.imavis.2006.05.014","article-title":"Wavelet moments for FARSI character recognition","volume":"25","author":"Broumandnia","year":"2007","journal-title":"Image and Vision Computing"},{"key":"10.3233\/JIFS-211242_ref14","doi-asserted-by":"crossref","first-page":"1712","DOI":"10.1016\/j.procs.2016.05.512","article-title":"New design based-SVM of the CNN classifier architecture with dropout for offline arabic handwritten recognition","volume":"80","author":"Elleuch","year":"2016","journal-title":"Procedia Computer Science"},{"key":"10.3233\/JIFS-211242_ref15","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.neucom.2017.02.105","article-title":"Chinese character captcha recognition and performance estimation via deep neural network","volume":"288","author":"Lin","year":"2018","journal-title":"Neurocomputing"},{"key":"10.3233\/JIFS-211242_ref16","doi-asserted-by":"crossref","first-page":"10603","DOI":"10.1109\/ACCESS.2018.2795104","article-title":"Ultilingual character segmentation and recognition schemes for indian document images","volume":"6","author":"Sahare","year":"2018","journal-title":"IEEE Access"},{"key":"10.3233\/JIFS-211242_ref17","first-page":"1","article-title":"Graph grammar models in syntactic pattern recognition","volume":"977","author":"Flasinski","year":"2019","journal-title":"Springer"},{"key":"10.3233\/JIFS-211242_ref18","doi-asserted-by":"crossref","unstructured":"Chaudhuri A. , Mandaviya K. , Badelia P. and Ghosh S.K. Optical character recognition systems for different languages with soft computing, Springer International Publishing (2017), 9\u201341.","DOI":"10.1007\/978-3-319-50252-6_2"},{"issue":"11","key":"10.3233\/JIFS-211242_ref20","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Radient-based learning applied to document recognition","volume":"86","author":"Cun","year":"1998","journal-title":"Proceedings of the IEEE,"},{"issue":"1","key":"10.3233\/JIFS-211242_ref22","doi-asserted-by":"crossref","first-page":"979","DOI":"10.3233\/JIFS-179463","article-title":"A general approach to fuzzy TOPSIS based on the concept of fuzzy multicriteria acceptability analysis","volume":"38","author":"Yatsalo","year":"2020","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/JIFS-211242_ref23","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1016\/j.jcde.2017.02.005","article-title":"Chaotic grey wolf optimization algorithm for constrained optimization problems","volume":"5","author":"Kohli","year":"2018","journal-title":"Journal of Computational Design and Engineering"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-211242","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:43:16Z","timestamp":1777455796000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-211242"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,15]]},"references-count":16,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.3233\/jifs-211242","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,15]]}}}