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DC Field | Value | Language |
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dc.contributor.author | P. M. Mahasantipiya | en_US |
dc.contributor.author | U. Yeesarapat | en_US |
dc.contributor.author | T. Suriyadet | en_US |
dc.contributor.author | J. Sricharoen | en_US |
dc.contributor.author | A. Dumrongwanich | en_US |
dc.contributor.author | T. Thaiupathump | en_US |
dc.date.accessioned | 2018-09-04T04:19:38Z | - |
dc.date.available | 2018-09-04T04:19:38Z | - |
dc.date.issued | 2011-07-26 | en_US |
dc.identifier.other | 2-s2.0-79960572166 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960572166&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/49877 | - |
dc.description.abstract | Forensic dentistry generally addresses the problem of identifying individuals based on the some specific characteristics of teeth or bite mark impressions. Bite mark identification process generally involves human interaction and has human bias. It would be beneficial to have a system that reduces human bias and has high accuracy matching performance. This paper describes a preliminary study to verify the effectiveness of applying the neural network approach in bite mark identification. By selecting some specific features of the bite marks for the model, trained networks give reasonable result for the matching accuracy in this initial study. | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.title | Bite mark identification using neural networks: A preliminary study | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011 | en_US |
article.volume | 1 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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