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Secrecy Analysis of Finite-Precision Compressive Cryptosystems.

, , and . IEEE Trans. Inf. Forensics Secur., (2020)

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Secrecy Analysis of Finite-Precision Compressive Cryptosystems., , and . IEEE Trans. Inf. Forensics Secur., (2020)Autoregressive process parameter estimation from compressed sensing measurements., and . ACSSC, page 488-492. IEEE, (2015)Learning mappings onto regularized latent spaces for biometric authentication., , , and . MMSP, page 1-6. IEEE, (2019)BioMetricNet: Deep Unconstrained Face Verification Through Learning of Metrics Regularized onto Gaussian Distributions., , , and . ECCV (25), volume 12370 of Lecture Notes in Computer Science, page 133-149. Springer, (2020)Autoregressive process parameters estimation from Compressed Sensing measurements and Bayesian dictionary learning.. Polytechnic University of Turin, Italy, (2016)base-search.net (ftpoltorinoiris:oai:iris.polito.it:11583/2642292).On the secrecy of compressive cryptosystems under finite-precision representation of sensing matrices., , and . ISCAS, page 1-4. IEEE, (2018)Energy obfuscation for compressive encryption and processing., , and . WIFS, page 1-6. IEEE, (2017)Distributed covariance estimation for compressive signal processing., and . ACSSC, page 676-680. IEEE, (2015)Authnet: Biometric Authentication Through Adversarial Learning., , , and . MLSP, page 1-6. IEEE, (2019)Compressive classification based on autoregressive features., and . COMM, page 433-438. IEEE, (2016)