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Legal Driver Age Prediction by using Deep Learning Approach

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dc.contributor.author Huzaifa Tariq, 01-134191-014
dc.contributor.author Umer Shaukat, 01-134191-030
dc.date.accessioned 2023-03-02T09:21:32Z
dc.date.available 2023-03-02T09:21:32Z
dc.date.issued 2023
dc.identifier.uri http://hdl.handle.net/123456789/15043
dc.description Supervised by Mr. Faisal Asad ur Rahman en_US
dc.description.abstract Classification of drivers in cars based on age using Facial images has proved to be a difficult task. The human face is one of the richest sources of information. The age of the driver can be used for law enforcement. Determining the age is difficult, As a result age classification has sparked interest among researchers. The goal here is to build a Convolutional Neural Network trained to classify images based on age and use it in automatic detection of underage drivers thereby decreasing the amount of manual work needed.Since stopping every car is time consuming and tedious work, automatic age prediction will improve efficiency and accuracy in identifying underage drivers en_US
dc.language.iso en en_US
dc.publisher Computer Sciences en_US
dc.relation.ispartofseries BS (CS);P-1800
dc.subject Legal Driver en_US
dc.subject Learning Approach en_US
dc.title Legal Driver Age Prediction by using Deep Learning Approach en_US
dc.type Project Reports en_US


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