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Energy-efficient neural image processing for Internet-of-Things edge devices.

, , , , , , , and . MWSCAS, page 1069-1072. IEEE, (2017)

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Dynamic Approximation with Feedback Control for Energy-Efficient Recurrent Neural Network Hardware., , and . ISLPED, page 168-173. ACM, (2016)Animal-Robot Interaction for pet caring., , , , and . CIRA, page 159-164. IEEE, (2009)Design and Analysis of a Neural Network Inference Engine Based on Adaptive Weight Compression., , , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 38 (1): 109-121 (2019)On the Design of Reliable 3D-ICs Considering Charged Device Model ESD Events During Die Stacking., and . DAC, page 27:1-27:6. ACM, (2014)Energy-efficient neural image processing for Internet-of-Things edge devices., , , , , , , and . MWSCAS, page 1069-1072. IEEE, (2017)Neurocube: Energy-Efficient Programmable Digital Deep Learning Accelerator based on Processor in Memory Platform.. Georgia Institute of Technology, Atlanta, GA, USA, (2019)base-search.net (ftgeorgiatech:oai:smartech.gatech.edu:1853/60660).Adaptive weight compression for memory-efficient neural networks., , , , and . DATE, page 199-204. IEEE, (2017)A power-aware digital feedforward neural network platform with backpropagation driven approximate synapses., , and . ISLPED, page 85-90. IEEE, (2015)Pulsed-latch ASIC synthesis in industrial design flow., , and . ASP-DAC, page 356-361. IEEE, (2013)A 159.2mW SoC implementation of T-DMB receiver including stacked memories., , , , , , , , , and . CICC, page 679-682. IEEE, (2008)