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Helmet Violation Processing Using Deep Learning

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dc.contributor.advisor Dailey, Matthew N.
dc.contributor.author K.C., Dharma Raj
dc.contributor.other Guha, Sumanta
dc.contributor.other Ekpanyapong, Mongkol
dc.date.accessioned 2017-04-27T01:50:44Z
dc.date.available 2017-04-27T01:50:44Z
dc.date.issued 2017-04-26
dc.identifier.other AIT
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/848
dc.description 91 p. en_US
dc.description.abstract Today, road accidents are one of the major causes of human deaths. Among the different type of road accidents, motorcycle accidents are common in Asia and cause severe injuries. The helmet is the main protection device for motorcyclists. Most countries have rules for use of helmets but many people fail to follow these rules for various reasons. One solution is a robust system that can find the motorcyclists who are violating helmet rules and record the evidence necessary for legal action. This thesis paper presents the use of deep convolutional neural networks (DCNNs) for finding motorcyclists who are violating helmet rules. I describe incremental development of a DCNN and an evaluation in terms of accuracy and speed for finding motorcyclists who are violating the helmet use rules. The license plate character DCNN provides highly accurate and fast character recognition of Thailand license plates. en_US
dc.description.sponsorship AIT Fellowship en_US
dc.language.iso en_US en_US
dc.publisher AIT en_US
dc.subject deep learning en_US
dc.subject convolutional neural networks en_US
dc.subject helmet violation classification en_US
dc.subject character recognition en_US
dc.title Helmet Violation Processing Using Deep Learning en_US
dc.type Thesis en_US

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