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In this paper we evaluate three state-of-the-art neural-network-based approaches for large-scale video classification, where the computational efficiency of the inference step is of particular importance due to the ever increasing amount of data throughput for video streams. Our evaluation focuses on finding good efficiency vs. accuracy tradeoffs by evaluating different network configurations and...
The end of Dennard scaling (i.e., the ability to shrink the feature size of integrated circuits while maintaining a constant power density) has now placed energy as a primary design principle in par with performance, all the way from the hardware to the application software. Along this line, optimizing the performance-energy balance of the 7/13 "dwarfs", introduced by UC Berkeley in 2006,...
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