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Deep Iris: Deep Learning for Gender Classification Through Iris Patterns
- Source :
- Acta Informatica Medica
- Publication Year :
- 2019
- Publisher :
- Academy of Medical sciences, 2019.
-
Abstract
- Introduction: One attractive research area in the computer science field is soft biometrics. Aim: To Identify a person’s gender from an iris image when such identification is related to security surveillance systems and forensics applications. Methods: In this paper, a robust iris gender-identification method based on a deep convolutional neural network is introduced. The proposed architecture segments the iris from a background image using the graph-cut segmentation technique. The proposed model contains 16 subsequent layers; three are convolutional layers for feature extraction with different convolution window sizes, followed by three fully connected layers for classification. Results: The original dataset consists of 3,000 images, 1,500 images for men and 1,500 images for women. The augmentation techniques adopted in this research overcome the overfitting problem and make the proposed architecture more robust and immune from simply memorizing the training data. In addition, the augmentation process not only increased the number of dataset images to 9,000 images for the training phase, 3,000 images for the testing phase and 3,000 images for the verification phase but also led to a significant improvement in testing accuracy, where the proposed architecture achieved 98.88%. A comparison is presented in which the testing accuracy of the proposed approach was compared with the testing accuracy of other related works using the same dataset. Conclusion: The proposed architecture outperformed the other related works in terms of testing accuracy.
- Subjects :
- Computer science
Iris recognition
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
Overfitting
01 natural sciences
Convolutional neural network
Field (computer science)
Deep Neural
Deep Learning
gender-identification
0103 physical sciences
0202 electrical engineering, electronic engineering, information engineering
Segmentation
Original Paper
010308 nuclear & particles physics
business.industry
Deep learning
Soft biometrics
Pattern recognition
General Medicine
Soft Biometrics
Deep Convolutional Neural Network
020201 artificial intelligence & image processing
Artificial intelligence
business
Subjects
Details
- Language :
- English
- ISSN :
- 19865988 and 03538109
- Volume :
- 27
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Acta Informatica Medica
- Accession number :
- edsair.doi.dedup.....e56d23b0d9912dc13145fa04a6cefb11