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VeDDS: Vehicle [car] Detector and Detailing System

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dc.contributor.author Srirangan, P
dc.date.accessioned 2022-03-14T07:30:13Z
dc.date.available 2022-03-14T07:30:13Z
dc.date.issued 2021
dc.identifier.citation Srirangan, P (2021) VeDDS: Vehicle [car] Detector and Detailing System. BSc. Dissertation Informatics Institute of Technology en_US
dc.identifier.issn 2017237
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/953
dc.description.abstract " Item location is utilized in numerous nations all throughout the planet, on account of a flood in interest somewhat recently. This paper centers around a dream based methodology that utilizes a convolutional neural organization for object recognition to distinguish vehicles progressively. The StandFord dataset is utilized to prepare an assembled YOLOv4-minuscule model to distinguish vehicles, and the model to the recognized items. AI is utilized to clarify each period of the preparation cycle, just as to battle overfitting and improve speed and precision. The creators had the option to improve the mean normal exactness, which is a measurement for deciding article finder precision." en_US
dc.language.iso en en_US
dc.title VeDDS: Vehicle [car] Detector and Detailing System en_US
dc.type Thesis en_US


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