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Toward Face Biometric De-identification using Adversarial Examples.

, , , , , , и . CoRR, (2023)

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Julian Gonska

Mikromechanische Biegebalken als hochsensitive Sensoren. Uni Freiburg, (2009)

Julian Grapengiesser

Mit Ungewissheit planen: eine Untersuchung verschiedener Ansätze der Handhabung von Ungewissheit in komplexen Planungsprozessen. Uni Stuttgart, (2009)

Julian Künzel

Rolle neurotroper und muskulotroper Spasmolytika in der In-vitro-Fertilisation (IVF): Untersuchungen am perfundierten Schweineuterus. Uni Erlangen-Nürnberg, (2009)

Julian Horst

Die verbindliche Auskunft nach § 89 Abgabenordnung. Uni Münster, (2009)

Julian Weichsel

 

Другие публикации лиц с тем же именем

Variable-length template protection based on homomorphic encryption with application to signature biometrics., , и . IWBF, стр. 1-6. IEEE, (2016)Mobile signature verification: feature robustness and performance comparison., , , и . IET Biom., 3 (4): 267-277 (2014)Guest editorial: Recent advances in representation learning for robust biometric recognition systems., , , , и . IET Biom., 11 (6): 531-533 (ноября 2022)mEBAL: A Multimodal Database for Eye Blink Detection and Attention Level Estimation., , , и . ICMI Companion, стр. 32-36. ACM, (2020)Are Adaptive Face Recognition Systems still Necessary? Experiments on the APE Dataset., , , и . IPAS, стр. 77-82. IEEE, (2020)Algorithmic Discrimination: Formulation and Exploration in Deep Learning-based Face Biometrics., , , , , и . SafeAI@AAAI, том 2560 из CEUR Workshop Proceedings, стр. 146-152. CEUR-WS.org, (2020)IFBiD: Inference-Free Bias Detection., , , , и . SafeAI@AAAI, том 3087 из CEUR Workshop Proceedings, CEUR-WS.org, (2022)MobileTouchDB: Mobile Touch Character Database in the Wild and Biometric Benchmark., , , , и . CVPR Workshops, стр. 2306-2314. Computer Vision Foundation / IEEE, (2019)Sensitive loss: Improving accuracy and fairness of face representations with discrimination-aware deep learning., , , и . Artif. Intell., (2022)Symbolic AI for XAI: Evaluating LFIT Inductive Programming for Explaining Biases in Machine Learning., , , , , , и . Comput., 10 (11): 154 (2021)