Computer vision based gender recognition using deep learning
| dc.contributor.author | Amirruddin Bin Abdul Razak | |
| dc.date.accessioned | 2021-02-23T02:10:46Z | |
| dc.date.available | 2021-02-23T02:10:46Z | |
| dc.date.issued | 2019-06 | |
| dc.description.abstract | The gender recognition system is useful for various purposes such as a screening process for face recognition based security surveillance. Recently, a lot of gender recognition system had been proposed and managed to achieve high accuracy on constrained images. However, these systems are generally based on a complex and big model and can only perform well on a constrained condition. Thus, this project focus on developing a gender recognition system for an unconstrained image including faces of people wearing a hijab, a hat and sunglasses while making sure that the system is fast and small. The system is divided into face detection and gender recognition. The face detection part uses MATLAB’s haar cascade detector. Improvement is made by applying pre-processing, median rejection and making multiple detections on the rotated image. The result shows that the precision and recall improved up to 92.54% and 91.85% respectively. For gender recognition, pre-trained AlexNet, GoogLeNet, ResNet-18, and VGGFace are trained using transfer learning and are tested on the aligned CelebA test set. The result shows that VGGFace model gives the highest accuracy at 96.65% which is higher than 95% accuracy obtained by the existing model. VGGFace model’s convolutional layer are then pruned and the result shows that the model speed almost doubled, and the model size is reduced by 35.49%. However, the accuracy drops to 96.53% but considering the improvement made, the accuracy drop is insignificant. Finally, both systems are combined and tested on CelebA test set and the accuracy of the pruned VGGFace model drop to 95.43% which shows that our system accuracy is limited by the face detection system. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/11445 | |
| dc.language.iso | en | en_US |
| dc.title | Computer vision based gender recognition using deep learning | en_US |
| dc.type | Other | en_US |
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