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This paper introduces a new handwritten TCR (HTCR) approach with two phases: (1) pre-processing and (2) classification. Primarily, the scanned document in the Tamil language is pre-processed via the steps like RGB to grayscale conversion, binarization with thresholding, image complementation, application of morphological operations and linearization. The pre-processed images are then classified using an optimized convolutional neural network (CNN) model. Further, the fully connected layer (FCL) and the weights are tuned optimally via a new sea lion with self-adaptiveness (SL-SA) algorithm. Lastly, the adopted model is evaluated using various measures to prove its supremacy over the existing schemes. <\/jats:p>","DOI":"10.1142\/s0218001422530032","type":"journal-article","created":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T07:41:01Z","timestamp":1655365261000},"source":"Crossref","is-referenced-by-count":6,"title":["Optimized Convolutional Neural Network for Tamil Handwritten Character Recognition"],"prefix":"10.1142","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9328-9207","authenticated-orcid":false,"given":"R.\u00a0Babitha","family":"Lincy","sequence":"first","affiliation":[{"name":"CCE Department, Sri Eshwar College of Engineering, Kinathukadavu, Coimbatore, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Gayathri","sequence":"additional","affiliation":[{"name":"ECE Department, Sri Venkateswara College of Engineering, Pennalur, Sriperumbudur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2022,8,15]]},"reference":[{"key":"S0218001422530032BIB001","doi-asserted-by":"publisher","DOI":"10.1007\/s11220-019-0231-5"},{"key":"S0218001422530032BIB002","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2018.07.155"},{"key":"S0218001422530032BIB003","doi-asserted-by":"publisher","DOI":"10.1016\/j.cogsys.2017.11.002"},{"key":"S0218001422530032BIB004","doi-asserted-by":"publisher","DOI":"10.1016\/j.lindif.2014.05.010"},{"key":"S0218001422530032BIB005","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2018.04.007"},{"key":"S0218001422530032BIB006","first-page":"288","volume-title":"AASRI Procedia \u2014 2013 AASRI Conf. 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