谭舜泉 Dr. Shunquan Tan 

工学博士、深圳大学副教授、特聘研究员、硕士生导师、IEEE Senior Member。

联系方式(Contact):

Email: tansq@szu.edu.cn
Tel：0755－86716669

地址：深圳市南山区白石路深圳大学电子与信息工程学院N801，计算机与软件学院935

简介(Biography)：

谭舜泉，男，博士，副教授，特聘研究员。2007年获中山大学计算机软件与理论专业博士学位。博士论文题目为“基于JPEG2000的图像隐写分析研究”。导师为中山大学信息科学与技术学院黄继武教授。2005年10月至2006年11月在美国新泽西理工学院担任访问学者一年。 在国内核心和重要期刊及国际会议上发表论文多篇。研究兴趣包括多媒体信息安全、机器学习、分布式数据库等。

Shunquan Tan received the B.S. degree in computational mathematics andapplied software and the Ph.D. degree in computer software and theoryfrom Sun Yat-sen University, Guangzhou, China, in 2002 and 2007,respectively. He was a Visiting Scholar with New Jersey Institute of Technology,Newark, NJ, USA, from 2005 to 2006.

He is currently an Associate Professor and Special-term researchfellow with College of Computer Science and Software Engineering, Shenzhen University, China.  He is also a member of the Shenzhen KeyLaboratory of Media Security.  He is IEEE senior member. His currentresearch interests include steganography, steganalysis, multimediaforensics, and deep machine learning.

研究兴趣(Research Interests)：

• 多媒体取证、多媒体安全、信息隐藏、图像/音频/视频信号处理、模式识别、机器学习；

• Multimedia Forensics and Security, Information Hiding,Image/Audio/Video Signal Processing, Pattern Recognition,Machine Learning；

研究生、博士后招生 (Recruitment)：

硕士生、博士后：计算机科学与技术、软件工程。

主讲课程(Teaching Courses)：

操作系统、离散数学。

科研项目 (Research Projects)：

• 国家自然科学基金面上项目“基于张量分解框架的深度学习信息隐藏对抗研究“，（61772349）  2018.0101-2021.12

• 国家自然科学基金青年基金 “大尺度分布式深度学习框架在隐写分析上的应用”，（61402295） 2015-2017.12

• 广东省深圳市基础研究项目 “基于大尺度分布式深度学习框架的隐写分析研究”，（JCYJ20140418182819173） 2014.09-2016.09

• 广东省育苗工程基金 “基于B样条曲线的针对内容自适应隐写术的隐写分析研究”，（2012LYM_0117） 2012.12-2014.12

学术成果(Publications)

部分期刊论文 Some Selected Journal Papers

• Q. Li, S. Chen, S. Tan*, B. Li, J. Huang. One-Class Double Compression Detection of Advanced Videos Based on Simple Gaussian Distribution Model [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2021, Early Access

• S. Tan, W. Wu, Z. Shao, Q. Li, B. Li, J. Huang. CALPA-NET: Channel-pruning-assisted Deep Residual Network for Steganalysis of Digital Images  [J]. IEEE Transactions on Information Forensics and Security, 2021, 16: 131-146
  

• Tan, Shunquan, et al. "CALPA-NET: Channel-Pruning-Assisted Deep Residual Network for Steganalysis of Digital Images." IEEE Transactions on Information Forensics and Security 16 (2020): 131-146；

• Hussain, Israr, Jishen Zeng, and Shunquan Tan. "A Survey on Deep Convolutional Neural Networks for Image Steganography and Steganalysis." KSII Transactions on Internet & Information Systems 14.3 (2020).

• Zhou, Ziling, Tan Shunquan, Zeng, Jishen, Chen, han, Hong, Shaobin. “Ensemble Deep Learning Features for Real-World Image Steganalysis.” KSII Transactions on Internet & Information Systems Accepted.
  

• Zeng, S. Tan*, B. Li, J. Huang, “Large-scale JPEG Image Steganalysis using Hybrid Deep-learning Framework,” IEEE Transactions on Information Forensics and Security, 2018, 13(5): 1242-1257.
  

• Tang,S. Tan*, B. Li, J. Huang, “Automatic Steganographic Distortion Learning Using a Generative Adversarial Network,” IEEE Signal Processing Letters, 2017，24(10): 1547–1551.

• Tan, H. Zhang, B. Li, J. Huang, “Pixel-Decimation-Assisted Steganalysis of Synchronize-Embedding-Changes Steganography”, IEEE Transactions on Information Forensics and Security, 2017, 12(7): 1658-1670.

• Chen, S. Tan*, B. Li, J. Huang, “Automatic Detection of Object-based Forgery in Advanced Video”, IEEE Transactions on Circuits and Systems for Video Technology , 2016, 26(11): 2138 – 2151.

• Li, T.-T. Ng, X. Li,S. Tan, J. Huang, “Statistical Model of JPEG Noises and Its Application in Quantization Step Estimation”, IEEE Transactions on Image Processing. 2015, 24(5): 1471–1484.

• Li, M. Wang, X. Li, S. Tan, J. Huang, “A Strategy of Clustering Modification Directions in Spatial Image Steganography”, IEEE Transactions on Information Forensics and Security. 2015, 10(9): 1905–1917.

• Li, T.-T. Ng, X. Li, S. Tan, J. Huang, “Revealing the Trace of High-quality JPEG Compression through Quantization Noise Analysis”, IEEE Transactions on Information Forensics and Security. 2015 10(3): 558-573.

• Li, S. Tan, M. Wang, J. Huang, “Investigation on Cost Assignment in Spatial Image Steganography”, IEEE Transactions on Information Forensics and Security. 2014 9(8): 1264–1277.

• Tan, B. Li, “Targeted Steganalysis of Edge Adaptive Image Steganography Based on LSB Matching Revisited Using B-spline Fitting”, IEEE Signal Processing Letters. 2012, 19(6): 336-339.

部分会议论文 Some Selected Conference Papers

• Zeng, S. Tan*, B. Li, “Pre-training via Fitting Deep Neural Network to Rich-model Features Extraction Procedure and Its Effect on Deep Learning for Steganalysis”, in Proc. Media Watermarking, Security, and Forensics, Part of IS&T International Symposium on Electronic Imaging (EI’2017), Burlingame, CA, 29 Juanuary-2 February, 2017.

• Tan, S. Chen, B. Li, “GOP Based Automatic Detection of Object-based Forgery in Advanced Video”, in Proc. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2015, HongKong, China, December 16-19, 2015.

• Tan, B. Li, “Stacked Convolutional Auto-Encoders for Steganalysis of Digital Images”, in Proc. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2014, Siem Reap, Cambodia, December 9-12, 2014.

• Tan, B. Li, “Targeted Steganalysis of Adaptive Pixel-value Differencing Steganography”, in Proc. 2012 IEEE International Conference on Image Processing. Orlando, Florida, USA, Oct. 2012.

专利 Patents

• 中国专利， 张浩杰，谭舜泉，李斌，黄继武，一种基于频域分析的图像隐写方法及系统，已公开，8.10，201610653147.X

• 中国专利， 曾吉申， 谭舜泉，李斌，黄继武，一种基于深度学习模型的隐写图像检测方法及系统，已公开，10.23，201610923908.9