Name
Abstract | ||
|---|---|---|
The performance of any biometric recognition system heavily dependents on finding a good and suitable feature representation space where observations from different classes are well separated. Unfortunately, finding this proper representation is a challenging problem which has taken a huge interest in machine learning and computer vision communities. In the this paper we present a comprehensive overview of the different existing feature representation techniques. This is carried out by introducing simple and clear taxonomies as well as effective explanation of the prominent techniques. This is intended to guide the neophyte and provide researchers with state-of-the-art approaches in order to help advance the research topic in biometrics. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s11042-018-6808-5 | Multimedia Tools and Applications |
Keywords | Field | DocType |
Biometrics, Feature representation, Dimensionality reduction, Feature selection, Decomposition learning | Dimensionality reduction,Pattern recognition,Recognition system,Feature selection,Computer science,Artificial intelligence,Biometrics,Machine learning | Journal |
Volume | Issue | ISSN |
79 | 7-8 | 1573-7721 |
Citations | PageRank | References |
1 | 0.35 | 58 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Imad Rida | 1 | 74 | 8.02 |
| Noor Almaadeed | 2 | 36 | 6.71 |
| Somaya Al-máadeed | 3 | 411 | 47.43 |
| Sambit Bakshi | 4 | 123 | 23.10 |