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20172022
most citedNPA: Neural News Recommendation with Personalized Attention

315 citations · 1.5k across the 58 of their papers we have counts for

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6 papers · 1 filter

cs.MM2019

Text Steganalysis with Attentional LSTM-CNN

YongJian Bao, Hao Yang, Zhongliang Yang +2

With the rapid development of Natural Language Processing (NLP) technologies, text steganography methods have been significantly innovated recently, which poses a great threat to c…

cs.MM2019★ 2 cited

FCEM: A Novel Fast Correlation Extract Model For Real Time Steganalysis of VoIP Stream via Multi-head Attention

Hao Yang, ZhongLiang Yang, YongJian Bao +2

Extracting correlation features between codes-words with high computational efficiency is crucial to steganalysis of Voice over IP (VoIP) streams. In this paper, we utilized attent…

cs.MM2019★ 26 cited

Fast Steganalysis Method for VoIP Streams

Hao Yang, ZhongLiang Yang, YongJian Bao +1

In this letter, we present a novel and extremely fast steganalysis method of Voice over IP (VoIP) streams, driven by the need for a quick and accurate detection of possible stegano…

cs.MM2019★ 3 cited

Hierarchical Representation Network for Steganalysis of QIM Steganography in Low-Bit-Rate Speech Signals

Hao Yang, Zhongliang Yang, YongJian Bao +1

With the Volume of Voice over IP (VoIP) traffic rises shapely, more and more VoIP-based steganography methods have emerged in recent years, which poses a great threat to the securi…

cs.MM2019★ 118 cited

TS-RNN: Text Steganalysis Based on Recurrent Neural Networks

Zhongliang Yang, Ke Wang, Jian Li +2

With the rapid development of natural language processing technologies, more and more text steganographic methods based on automatic text generation technology have appeared in rec…

cs.MM2019★ 5 cited

Real-Time Steganalysis for Stream Media Based on Multi-channel Convolutional Sliding Windows

Zhongliang Yang, Hao Yang, Yuting Hu +2

Previous VoIP steganalysis methods face great challenges in detecting speech signals at low embedding rates, and they are also generally difficult to perform real-time detection, m…