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https://hdl.handle.net/10356/13335
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Low, Siew Eng. | en_US |
dc.date.accessioned | 2008-10-20T07:25:24Z | - |
dc.date.available | 2008-10-20T07:25:24Z | - |
dc.date.copyright | 1998 | en_US |
dc.date.issued | 1998 | en_US |
dc.identifier.uri | http://hdl.handle.net/10356/13335 | - |
dc.description.abstract | In this project, two learning schemes had been tested and verified, in the recognition unit within the image processing environment of the Machine Vision Tool, namely the Bayes classifier method and the neural network-error back propagation gradient descent learning method. Their performances were analysed and compared. Sometimes the algorithms, especially the Bayes classifier method, fail to distinguish between two characters that are inherently similar, such as 'S" and '5', 'B' and '8'. | en_US |
dc.format.extent | 130 p. | en_US |
dc.language.iso | en | en_US |
dc.subject | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing | en_US |
dc.title | Comparison of character recognition performance - bayes classifier and neural network methods | en_US |
dc.type | Thesis | en_US |
dc.contributor.supervisor | Chan, Kap Luk | en_US |
dc.contributor.school | School of Electrical and Electronic Engineering | en_US |
dc.description.degree | Master of Science (Computer Control and Automation) | en_US |
item.grantfulltext | restricted | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | EEE Theses |
Files in This Item:
File | Description | Size | Format | |
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LowSiewEng1998.pdf Restricted Access | Main report | 11.18 MB | Adobe PDF | View/Open |
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