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New Passive and Active Attacks on Deep Neural Networks in Medical Applications.

, , , , , , , and . ICCAD, page 39:1-39:9. IEEE, (2020)

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SCADET: a side-channel attack detection tool for tracking prime+probe., , , and . ICCAD, page 107. ACM, (2018)A Power-Efficient FPGA-Based Mixture-of-Gaussian (MoG) Background Subtraction for Full-HD Resolution., , and . FCCM, page 241. IEEE Computer Society, (2014)Taming the Memory Demand Complexity of Adaptive Vision Algorithms., , and . IESS, volume 523 of IFIP Advances in Information and Communication Technology, page 145-158. Springer, (2015)Evaluating Fault Resiliency of Compressed Deep Neural Networks., , , and . ICESS, page 1-7. IEEE, (2019)An efficient architecture solution for low-power real-time background subtraction., , and . ASAP, page 218-225. IEEE Computer Society, (2015)Power-efficient real-time solution for adaptive vision algorithms., , and . IET Comput. Digit. Tech., 9 (1): 16-26 (2015)GPU Overdrive Fault Attacks on Neural Networks., , and . ICCAD, page 1-8. IEEE, (2021)New Passive and Active Attacks on Deep Neural Networks in Medical Applications., , , , , , , and . ICCAD, page 39:1-39:9. IEEE, (2020)Power Side-Channel Vulnerability Assessment of Lightweight Cryptographic Scheme, XOODYAK., , , , , , , , , and . DAC, page 1-6. IEEE, (2023)A Novel GPU Overdrive Fault Attack., , and . DAC, page 1-6. IEEE, (2020)