Learning and transferring representations for image steganalysis using convolutional neural network
文献类型：会议论文
| 作者 | Qian, Yinlong; Dong, Jing ; Wang, Wei; Tan, Tieniu
|
| 出版日期 | 2016 |
| 会议日期 | September 25–28, 2016 |
| 会议地点 | Phoenix, Arizona, USA |
| 关键词 | Convolutional Neural Network Steganalysis Deep Learning Transfer Learning |
| 英文摘要 | The major challenge of machine learning based image steganalysis lies in obtaining powerful feature representations. Recently, Qian et al. have shown that Convolutional Neural Network (CNN) is effective for learning features automatically for steganalysis. In this paper, we follow up this new paradigm in steganalysis, and propose a framework based on transfer learning to help the training of CNN for steganalysis, hence to achieve a better performance. We show that feature representations learned with a pre-trained CNN for detecting a steganographic algorithm with a high payload can be efficiently transferred to improve the learning of features for detecting the same steganographic algorithm with a low pay-load. By detecting representative WOW and S-UNIWARD steganographic algorithms, we demonstrate that the proposed scheme is effective in improving the feature learning in CNN models for steganalysis. |
| 会议录 | Proceedings of 2016 IEEE International Conference on Image Processing
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12306]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Dong, Jing |
| 推荐引用方式 GB/T 7714 | Qian, Yinlong,Dong, Jing,Wang, Wei,et al. Learning and transferring representations for image steganalysis using convolutional neural network[C]. 见:. Phoenix, Arizona, USA. September 25–28, 2016. |
入库方式： OAI收割
来源：自动化研究所
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