A Systematic Literature Review on Face Morphing Attack Detection (MAD)
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-93453-8_7
Reference110 articles.
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2. Wandzik L, Garcia RV, Kaeding G, Chen X (2017) CNNs under attack: on the vulnerability of deep neural networks based face recognition to image morphing. In: Kraetzer C, Shi Y-Q, Dittmann J, Kim HJ (eds) Digital forensics and watermarking, vol 10431. Springer International Publishing, Cham, pp 121–135. https://doi.org/10.1007/978-3-319-64185-0_10
3. Olanrewaju L, Oyebiyi O, Misra S, Maskeliunas R, Damasevicius R (2020) Secure ear biometrics using circular kernel principal component analysis, Chebyshev transform hashing and Bose–Chaudhuri–Hocquenghem error-correcting codes. Signal Image Video Process 14(5):847–855. https://doi.org/10.1007/s11760-019-01609-y
4. Ramachandra R, Venkatesh S, Raja K, Busch C (2020) Detecting face morphing attacks with collaborative representation of steerable features. In: Chaudhuri BB, Nakagawa M, Khanna P, Kumar S (eds) Proceedings of 3rd international conference on computer vision and image processing, vol 1022. Springer, Singapore, pp 255–265. https://doi.org/10.1007/978-981-32-9088-4_22
5. Wu J (2011) Face recognition jammer using image morphing. Boston University, Saint Mary’s Street, Boston, ECE-2011-03
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