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The classification was performed using deep learning techniques, out of which 70%\u201330% was used for training and validation purposes. The proposed method was thoroughly evaluated on a dataset collected from visually impaired people using Deep Learning (DL) techniques. The results obtained from deep learning techniques are compared with classical machine learning techniques like Na\u00efve Bayes (NB), Decision Trees (DT), SVM, and KNN. We divided the multi-class into two categories, i.e., Category-A (a\u2013m) and Category-B (n\u2013z). The performance was evaluated using Sensitivity, Specificity, Positive Predicted Value (PPV), Negative Predicted Value (NPV), False Positive Rate (FPV), Total Accuracy (TA), and Area under the Curve (AUC). GoogLeNet Model, followed by the Sequential model, SVM, DT, KNN, and NB achieved the highest performance. The results prove that the proposed Braille input method for touch screen devices is more effective and that the deep learning method can predict the user's input with high accuracy.<\/jats:p>","DOI":"10.1186\/s13673-020-00246-6","type":"journal-article","created":{"date-parts":[[2020,9,19]],"date-time":"2020-09-19T10:02:34Z","timestamp":1600509754000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Deep learning scheme for character prediction with position-free touch screen-based Braille input method"],"prefix":"10.1186","volume":"10","author":[{"given":"Sana","family":"Shokat","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rabia","family":"Riaz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sanam Shahla","family":"Rizvi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdul Majid","family":"Abbasi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adeel Ahmed","family":"Abbasi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6295-7014","authenticated-orcid":false,"given":"Se Jin","family":"Kwon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,19]]},"reference":[{"key":"246_CR1","unstructured":"Latest Global Blindness and VI prevalence figures published in Lancet Vision Atlas. https:\/\/atlas.iapb.org\/news\/latest-global-blindness-vi-prevalence-figures-published-lancet\/\/. 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