Name
Abstract | ||
|---|---|---|
With the emergence of the generation-based steganography, the traditional text steganalysis methods show the unsatisfactory detection performance as the manually extracted features are simple and non-universal. The recently proposed deep learning-based text steganalysis methods can obtain the great detection accuracy by extracting the high-level features. In this letter, a hybrid text steganalysis... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LSP.2019.2953953 | IEEE Signal Processing Letters |
Keywords | Field | DocType |
Feature extraction,Semantics,Convolution,Kernel,Training,Neural networks,Deep learning | Pattern recognition,Artificial intelligence,Steganalysis,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
26 | 12 | 1070-9908 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Niu | 1 | 22 | 9.44 |
| Juan Wen | 2 | 11 | 3.17 |
| Ping Zhong | 3 | 10 | 3.16 |
| Yiming Xue | 4 | 17 | 6.28 |