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Emulation-based hierarchical fault-injection framework for coarse-to-fine vulnerability analysis of hardware-accelerated approximate algorithms.

, , , , and . DATE, page 830-833. IEEE, (2016)

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In-field vulnerability analysis of hardware-accelerated computer vision applications., , , , and . FPL, page 1-4. IEEE, (2015)Emulation-based hierarchical fault-injection framework for coarse-to-fine vulnerability analysis of hardware-accelerated approximate algorithms., , , , and . DATE, page 830-833. IEEE, (2016)Edge Intelligence: Challenges and Opportunities of Near-Sensor Machine Learning Applications., , , and . ASAP, page 1-7. IEEE Computer Society, (2018)Deep Learning for Edge Computing: Current Trends, Cross-Layer Optimizations, and Open Research Challenges., , , , , , and . ISVLSI, page 553-559. IEEE, (2019)An embedded hardware-efficient architecture for real-time cascade Support Vector Machine classification., , and . ICSAMOS, page 129-136. IEEE, (2013)Real-Time Obstacle Avoidance for Mobile Robots via Stereoscopic Vision Using Reconfigurable Hardware (Abstract Only)., , , and . FPGA, page 262. ACM, (2015)Embedded Hardware-Efficient Real-Time Classification With Cascade Support Vector Machines., , , and . IEEE Trans. Neural Netw. Learning Syst., 27 (1): 99-112 (2016)Distributed adaptive task allocation for energy conservation in camera sensor networks., , , and . ICDSC, page 92-97. ACM, (2015)Cooperative fault-tolerant target tracking in Camera Sensor Networks., , , , , and . ICC, page 6634-6639. IEEE, (2015)Efficient ConvNet-based Object Detection for Unmanned Aerial Vehicles by Selective Tile Processing., , and . CoRR, (2019)