Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/3682
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dc.contributor.authorNoor ul Ain-
dc.date.accessioned2018-02-19T15:12:11Z-
dc.date.available2018-02-19T15:12:11Z-
dc.date.issued2012-
dc.identifier.urihttp://hdl.handle.net/123456789/3682-
dc.description.abstractOptical Mark Recognition (also called Optical Mark Reading and OMR) is the automated process of capturing the human-marked data which is in the form of bubbles, squares or tick marks. This technique is widely used in various applications like exam evaluation, automated attendance marking, community surveys etc. Many traditional OMR (Optical Mark Recognition) devices make use of commercially available dedicated OMR scanners and use especially designed thick sheets. The present work proposes to automate the test checking on a desktop computer using ordinary scanner. Machine learning algorithm is used to recognize marked answers on scanned images, classificationen_US
dc.language.isoenen_US
dc.publisherQuaid-i-Azam University, Islamabaden_US
dc.relation.ispartofseriesFaculty of Natural Sciences;-
dc.subjectComputer Sciencesen_US
dc.titleOptical Mark Recognizer for QAU Entry Test Checking.en_US
dc.typeThesisen_US
Appears in Collections:M.Sc

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