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ApesNet: a pixel-wise efficient segmentation network for embedded devices., , , , and . IET Cyper-Phys. Syst.: Theory & Appl., 1 (1): 78-85 (2016)Low-Power Computer Vision: Status, Challenges, Opportunities., , , , , , , , , and 34 other author(s). CoRR, (2019)ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition., , , , , , , and . CoRR, (2020)Low-Power Computer Vision: Status, Challenges, and Opportunities., , , , , , , , , and 34 other author(s). IEEE J. Emerg. Sel. Topics Circuits Syst., 9 (2): 411-421 (2019)AutoShrink: A Topology-aware NAS for Discovering Efficient Neural Architecture., , , , , , and . CoRR, (2019)Adversarial Attack: A New Threat to Smart Devices and How to Defend It., , , , , , and . IEEE Consumer Electron. Mag., 9 (4): 49-55 (2020)Understanding the design of IBM neurosynaptic system and its tradeoffs: A user perspective., , , , , and . DATE, page 139-144. IEEE, (2017)AdverQuil: an efficient adversarial detection and alleviation technique for black-box neuromorphic computing systems., , , , , and . ASP-DAC, page 518-525. ACM, (2019)ApesNet: A Pixel-wise Efficient Segmentation Network., , , , and . ESTIMedia, page 2-8. ACM, (2016)AutoShrink: A Topology-Aware NAS for Discovering Efficient Neural Architecture., , , , , , and . AAAI, page 6829-6836. AAAI Press, (2020)