Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/10595
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dc.contributor.authorPariyani, Bhavesh M.-
dc.date.accessioned2022-02-03T07:05:18Z-
dc.date.available2022-02-03T07:05:18Z-
dc.date.issued2021-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/10595-
dc.description.abstractDefect Detection on Rail head surface is a major issue for railway transportation. Rail maintenance of railway track is necessary to avoid any railway accidents due to the defects on railway track surface. Since rail surface defects have such a wide range of characteristics, it’s difficult to categorize them using machine learning. In this project machine vision-based defect detection was implemented using Deep learning-based object detection and semantic segmentation. Image enhancement techniques were also implemented which helped in making an efficient deep learning model in training.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries19MCED09;-
dc.subjectComputer 2019en_US
dc.subjectProject Reporten_US
dc.subjectComputer Project Reporten_US
dc.subjectProject Report 2019en_US
dc.subject19MCEen_US
dc.subject19MCEDen_US
dc.subject19MCED09en_US
dc.subjectCE (DS)en_US
dc.subjectDS 2019en_US
dc.titleRailway Track Defect Detection using Machine Visionen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, CE (DS)

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