The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Fusion of face and speech data for person identity verification
Open accessAbstract
Biometric person identity authentication is gaining more and more attention. The authentication task performed by an expert is a binary classification problem: reject or accept identity claim. Combining experts, each based on a different modality (speech, face, fingerprint, etc.), increases the performance and robustness of identity authentication systems. In this context, a key issue is the fusion of the different experts for taking a final decision (i.e., accept or reject identity claim). We propose to evaluate different binary classification schemes (support vector machine, multilayer perceptron, C4.5 decision tree, Fisher's linear discriminant, Bayesian classifier) to carry on the fusion. The experimental results show that support vector machines and Bayesian classifier achieve almost the same performances, and both outperform the other evaluated classifiers.
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Cited by
An introduction to biometric recognition
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Recent advances in visual and infrared face recognition—a review
Kong, S. G., Heo, J., Abidi, B. R., Paik, J., & Abidi, M. A. (2005) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2004.04.001 · Cited by 586
Personal Verification Using Palmprint and Hand Geometry Biometric
Kumar, A., Wong, D. C. M., Shen, H. C., & Jain, A. K. (2003) · Lecture Notes in Computer Science · doi:10.1007/3-540-44887-x_78 · Cited by 502
Metadata
- Authors
- Ben-Yacoub, S., Abdeljaoued, Y., & Mayoraz, E.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 1999
- Volume
- 10
- Issue
- 5
- Pages
- 1065-1074
- ISSN
- 1045-9227 (ISSN-L)
- OpenAlex
- W2119970915
- Cited by
- 334
- References
- 31
- FWCI
- 13.13
- Type
- journal article
- Language
- en
- Open access
- green
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