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A Cognitive Model of Character Recognition Using Support Vector Machines
Authors: K. Freedman
Abstract:In the present study, a support vector machine (SVM) learning approach to character recognition is proposed. Simple feature detectors, similar to those found in the human visual system, were used in the SVM classifier. Alphabetic characters were rotated to 8 different angles and using the proposed cognitive model, all characters were recognized with 100% accuracy and specificity. These same results were found in psychiatric studies of human character recognition.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1079820Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1513
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