Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10181
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dc.contributor.authorKumar, Gulshan-
dc.contributor.authorSharma, Vipul [Guided by]-
dc.date.accessioned2023-09-30T08:53:29Z-
dc.date.available2023-09-30T08:53:29Z-
dc.date.issued2023-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10181-
dc.descriptionEnrollment No. 191341en_US
dc.description.abstractThe major purpose of our project to dectect object using faster R-CNN to develop a technique for programmed object finding and counting on throughways. Our method does not rely on foundation; rather, it employs a channel through which we identify and count the cars, record a video or a photograph, and then make a decision to give the total number of object. The purpose of this approach is to create a superior object detector structure inside the project for smoother detection of object flow and to increase a overall efficiency.en_US
dc.language.isoen_USen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectObject detectionen_US
dc.subjectNeural networken_US
dc.subjectMachine learningen_US
dc.subjectDeep learningen_US
dc.titleSaliency Guided Faster R-CNN for object detection and Recognitionen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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