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SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size, , , , , and . (2016)cite arxiv:1602.07360Comment: In ICLR Format.A Double Disturbance Observer Design for Compensation of Unknown Time Delay in a Wireless Motion Control System., , , , , , and . IEEE Trans. Control. Syst. Technol., 26 (2): 675-683 (2018)Energy Efficient Residual Energy Monitoring in Wireless Sensor Networks., and . Int. J. Distributed Sens. Networks, 5 (6): 748-770 (2009)Trained Ternary Quantization., , , and . ICLR (Poster), OpenReview.net, (2017)Once-for-All: Train One Network and Specialize it for Efficient Deployment., , , , and . ICLR, OpenReview.net, (2020)Energy Efficient On-Demand Dynamic Branch Prediction Models., , , , , and . IEEE Trans. Computers, 69 (3): 453-465 (2020)Angel-Eye: A Complete Design Flow for Mapping CNN Onto Embedded FPGA., , , , , , , , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 37 (1): 35-47 (2018)Learning both Weights and Connections for Efficient Neural Networks., , , and . CoRR, (2015)Domain-specific hardware accelerators., , and . Commun. ACM, 63 (7): 48-57 (2020)SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size., , , , , and . CoRR, (2016)