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Scaling up Artificial Intelligence (AI) algorithms for massive datasets to improve their performance is becoming crucial. In Machine Translation (MT), one of most important research fields of AI, models based on Recurrent Neural Net- works (RNN) show state-of-the-art performance in recent years, and many researchers keep working on improving RNN-based models to achieve better accuracy in translation...
The real-time requirements of hardwired HEVC encoder demand that, at the grain of coding tree unit (CTU), the maximum computation should be reduced by a fast CU mode decision algorithm. In addition, to realize the parallel rate-distortion optimization (RDO) of different CU modes, the current CU mode decision should not use the auxiliary information from other CU modes. Considering the above constraints,...
Classifying encrypted traffic is critical to effective network analysis and management. While traditional payload- based methods are powerless to deal with encrypted traffic, machine learning methods have been proposed to address this issue. However, these methods often bring heavy overhead into the system. In this paper, we propose a hybrid method that combines signature-based methods and statistical...
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