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dc.contributor.authorChatterjee, Anirban
dc.date.accessioned2018-12-10T17:35:17Z
dc.date.available2018-12-10T17:35:17Z
dc.date.issued2018-11-07
dc.identifier.urihttp://hdl.handle.net/1853/60606
dc.descriptionPresented on November 7, 2018 at 6:00 p.m. in the Georgia Tech Hotel and Conference Center, room 236.en_US
dc.descriptionAnirban Chatterjee is a PhD student in Computational Science and Engineering at Georgia Tech. His research focuses on the automated assessment of road infrastructure condition using computer vision.en_US
dc.descriptionRuntime: 02:51 minutesen_US
dc.format.extent02:51 minutes
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesThree Minute Thesis (3MT™) at Georgia Techen_US
dc.relation.ispartofseries3MT 2018 Finalsen_US
dc.subjectLaser scannersen_US
dc.subjectPavement condition assessmenten_US
dc.subjectRoad conditionen_US
dc.subjectSmartphonesen_US
dc.titleFusion of emerging technologies for robust, frequent and cost-effective road infrastructure condition assessmenten_US
dc.typePresentationen_US
dc.typeVideoen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Office of Graduate Studiesen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Teaching and Learningen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Civil and Environments Engineeringen_US


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