Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/49877
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dc.contributor.authorP. M. Mahasantipiyaen_US
dc.contributor.authorU. Yeesarapaten_US
dc.contributor.authorT. Suriyadeten_US
dc.contributor.authorJ. Sricharoenen_US
dc.contributor.authorA. Dumrongwanichen_US
dc.contributor.authorT. Thaiupathumpen_US
dc.date.accessioned2018-09-04T04:19:38Z-
dc.date.available2018-09-04T04:19:38Z-
dc.date.issued2011-07-26en_US
dc.identifier.other2-s2.0-79960572166en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960572166&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/49877-
dc.description.abstractForensic 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.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleBite mark identification using neural networks: A preliminary studyen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleIMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011en_US
article.volume1en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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