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http://hdl.handle.net/123456789/3682
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DC Field | Value | Language |
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dc.contributor.author | Noor ul Ain | - |
dc.date.accessioned | 2018-02-19T15:12:11Z | - |
dc.date.available | 2018-02-19T15:12:11Z | - |
dc.date.issued | 2012 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/3682 | - |
dc.description.abstract | Optical 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, classification | en_US |
dc.language.iso | en | en_US |
dc.publisher | Quaid-i-Azam University, Islamabad | en_US |
dc.relation.ispartofseries | Faculty of Natural Sciences; | - |
dc.subject | Computer Sciences | en_US |
dc.title | Optical Mark Recognizer for QAU Entry Test Checking. | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | M.Sc |
Files in This Item:
File | Description | Size | Format | |
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COM 2001.pdf | COM 2001 | 616.59 kB | Adobe PDF | View/Open |
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