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ir.bowen.edu.ng:8181/jspui/handle/123456789/1033| Title: | Fingerprint phenotyping for ethnicity classification: A generative deep learning perspective |
| Authors: | Falohun, A. S. Aworinde, H. O. Afolabi, A. O. Ismaila, W. O. Fenwa, O. D. |
| Keywords: | Deep learning Fingerprint classification Ethnicity identification Recognition accuracy |
| Issue Date: | 2018 |
| Publisher: | An International Journal of Biological and Physical Sciences |
| Citation: | Falohun A.S ., Aworinde, H. O., Afolabi, A. O. Ismaila, W. O. & Fenwa, O.D. (2018). Fingerprint phenotyping for ethnicity classification: A generative deep learning perspective. An International Journal of Biological and Physical Sciences, 23(1), 84 - 90. |
| Abstract: | In recent years, deep learning techniques have already been impacting wide range of information processing, pattern recognition, image processing and computer vision related works within the traditional and widened scopes. Hence, this research explored a generative deep architecture approach to better engage soft and hard biometric features for identification and classification of individual persons into their respective ethnic divides. |
| URI: | ir.bowen.edu.ng:8080/jspui/handle/123456789/1033 |
| Appears in Collections: | Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 29.pdf | Fingerprint Phenotyping for Ethnicity Classification: A Generative Deep Learning Perspective | 4.34 MB | Adobe PDF | View/Open |
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