A Novel Fingerprint Recovery Scheme using Deep Neural Network-based Learning-Reference-Cited by-同舟云学术

A Novel Fingerprint Recovery Scheme using Deep Neural Network-based Learning

Published:2020-06-16 Issue:26-27 Volume:80 Page:34121-34135
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Lee Samuel,Jang Seok-Woo,Kim Dongho,Hahn Hernsoo,Kim Gye-Young

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-020-09157-1.pdf

Reference43 articles.

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2. Bansal R, Sehgal P, Bedi P (2011) Minutiae Extraction from Fingerprint Images - a review. IJSCI International Jounal of Computer Science Issues 8(5):74–85

3. Bontrager, P., Roy, A., Togelius, J., Memon, N., Ross, A. (2018) DeepMasterPrints: generating MasterPrints for dictionary attacks via latent variable evolution. In Proc. of the IEEE 9th international conference on biometrics theory, applications and systems (BTAS), Redondo Beach, USA, 1-9. DOI: https://doi.org/10.1109/BTAS.2018.8698539

4. Cai H, Yang Z, Cao X, Xia W, Xu X (2014) New iterative triclass thresholding technique in image segmentation. IEEE trans. Image process 23(3):1038–1046. https://doi.org/10.1109/TIP.2014.2298981

5. Ding, S., Wallin, A. (2019) Towards recovery of conditional vectors from conditional generative adversarial networks. Pattern Recogn. Lett. 122:66-72. DOI: 10.1016/j.patrec.2019.02.020

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