The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Deep Representations for Iris, Face, and Fingerprint Spoofing Detection
Open accessAbstract
Biometrics systems have significantly improved person identification and authentication, playing an important role in personal, national, and global security. However, these systems might be deceived (or spoofed) and, despite the recent advances in spoofing detection, current solutions often rely on domain knowledge, specific biometric reading systems, and attack types. We assume a very limited knowledge about biometric spoofing at the sensor to derive outstanding spoofing detection systems for iris, face, and fingerprint modalities based on two deep learning approaches. The first approach consists of learning suitable convolutional network architectures for each domain, whereas the second approach focuses on learning the weights of the network via back propagation. We consider nine biometric spoofing benchmarks - each one containing real and fake samples of a given biometric modality and attack type - and learn deep representations for each benchmark by combining and contrasting the two learning approaches. This strategy not only provides better comprehension of how these approaches interplay, but also creates systems that exceed the best known results in eight out of the nine benchmarks. The results strongly indicate that spoofing detection systems based on convolutional networks can be robust to attacks already known and possibly adapted, with little effort, to image-based attacks that are yet to come.
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Fingerprint Liveness Detection Using Convolutional Neural Networks
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Iris Recognition With Off-the-Shelf CNN Features: A Deep Learning Perspective
Nguyen, K., Fookes, C., Ross, A., & Sridharan, S. (2018) · IEEE Access · doi:10.1109/access.2017.2784352 · Cited by 355
Convolutional Neural Network for Finger-Vein-Based Biometric Identification
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Metadata
- Authors
- Menotti, D., Chiachia, G., Pinto, A., Robson Schwartz, W., Pedrini, H., Xavier Falcao, A., & Rocha, A.
- Venue
- IEEE Transactions on Information Forensics and Security
- Published
- 2015-04
- Volume
- 10
- Issue
- 4
- Pages
- 864-879
- ISSN
- 1556-6013 (ISSN-L)
- 1556-6021
- OpenAlex
- W2136975665
- Cited by
- 485
- References
- 48
- FWCI
- 60.27
- Type
- journal article
- Language
- en
- Open access
- green
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- Menotti, D., Chiachia, G., Pinto, A., Robson Schwartz, W., Pedrini, H., Xavier Falcao, A., & Rocha, A. (2015). Deep Representations for Iris, Face, and Fingerprint Spoofing Detection. IEEE Transactions on Information Forensics and Security. https://doi.org/10.1109/tifs.2015.2398817
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