| 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 |