Name
Title | ||
|---|---|---|
Convolutional neural networks for gender prediction from smartphone-based ocular images. |
Abstract | ||
|---|---|---|
Automated gender prediction has drawn significant interest in numerous applications such as surveillance, human-computer interaction, anonymous customised advertisement system, image retrieval system, and biometrics. In the context of smartphone devices, gender information has been used to enhance the accuracy of the integrated biometric authentication and mobile healthcare system. Here, the autho... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1049/iet-bmt.2017.0171 | IET Biometrics |
Keywords | Field | DocType |
biometrics (access control),convolution,feature extraction,feedforward neural nets,gender issues,health care,human computer interaction,image classification,image colour analysis,image retrieval,learning (artificial intelligence),neural net architecture,smart phones | Computer vision,Computer science,Convolutional neural network,Image retrieval,Artificial intelligence,RGB color model,Deep learning,Biometrics,Healthcare system | Journal |
Volume | Issue | ISSN |
7 | 5 | 2047-4938 |
Citations | PageRank | References |
4 | 0.38 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ajita Rattani | 1 | 266 | 17.85 |
| Narsi Reddy | 2 | 8 | 2.80 |
| Reza Derakhshani | 3 | 166 | 21.08 |