Artificial intelligence, Algorithm, Digital watermarking, Computer vision and Pattern recognition are his primary areas of study. His studies deal with areas such as Image quality, Theoretical computer science, Discrete cosine transform, Information hiding and Steganography as well as Algorithm. His Discrete cosine transform study deals with JPEG intersecting with Steganalysis.
As a part of the same scientific study, Yun Q. Shi usually deals with the Digital watermarking, concentrating on Watermark and frequently concerns with Copy protection, Speech recognition and Adaptive filter. His study on Image compression, Feature extraction and Image-based modeling and rendering is often connected to 2D computer graphics as part of broader study in Computer vision. He has included themes like Histogram, Image, Distance measurement and Markov process in his Pattern recognition study.
Yun Q. Shi spends much of his time researching Artificial intelligence, Computer vision, Algorithm, Digital watermarking and Pattern recognition. His studies in JPEG, Discrete cosine transform, Data compression, Steganalysis and Wavelet are all subfields of Artificial intelligence research. Yun Q. Shi usually deals with JPEG and limits it to topics linked to Steganography and Hilbert–Huang transform.
His research integrates issues of Theoretical computer science, Information hiding, Embedding, Speech recognition and Interleaving in his study of Algorithm. His Digital watermarking research incorporates elements of Watermark, Binary image, Robustness and Signal processing. He combines subjects such as Contextual image classification, Thresholding and Standard test image with his study of Pattern recognition.
His primary areas of study are Artificial intelligence, Algorithm, Embedding, Information hiding and Computer vision. Much of his study explores Artificial intelligence relationship to Pattern recognition. His study on Algorithm also encompasses disciplines like
His Embedding study integrates concerns from other disciplines, such as Histogram, Theoretical computer science and Line. His Information hiding research is multidisciplinary, incorporating elements of Motion vector and Encryption. Many of his research projects under Computer vision are closely connected to Uncompressed video with Uncompressed video, tying the diverse disciplines of science together.
Yun Q. Shi mainly focuses on Algorithm, Theoretical computer science, Artificial intelligence, Embedding and Steganalysis. Algorithm and Information hiding are commonly linked in his work. His Information hiding study which covers Cryptography that intersects with Codec.
Yun Q. Shi undertakes interdisciplinary study in the fields of Artificial intelligence and Object detection through his works. The study incorporates disciplines such as Trellis modulation and Discrete cosine transform in addition to Embedding. Yun Q. Shi has researched Steganalysis in several fields, including Feature, Pooling, Artificial neural network, Feature vector and Convolutional neural network.
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Reversible Watermarking Algorithm Using Sorting and Prediction
V. Sachnev;Hyoung Joong Kim;Jeho Nam;S. Suresh.
IEEE Transactions on Circuits and Systems for Video Technology (2009)
Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards
Yun Q. Shi;Huifang Sun.
A survey on image steganography and steganalysis
Bin Li;Junhui He;Jiwu Huang;Yun Qing Shi.
multimedia signal processing (2011)
A Markov process based approach to effective attacking JPEG steganography
Yun Q. Shi;Chunhua Chen;Wen Chen.
information hiding (2006)
A DWT-DFT composite watermarking scheme robust to both affine transform and JPEG compression
Xiangui Kang;Jiwu Huang;Yun Q Shi;Yan Lin.
IEEE Transactions on Circuits and Systems for Video Technology (2003)
A Novel Difference Expansion Transform for Reversible Data Embedding
Hyoung Joong Kim;V. Sachnev;Yun Qing Shi;Jeho Nam.
IEEE Transactions on Information Forensics and Security (2008)
Distortionless data hiding based on integer wavelet transform
Guorong Xuan;Jiang Zhu;Jidong Chen;Yun Q. Shi.
Electronics Letters (2002)
A generalized Benford's law for JPEG coefficients and its applications in image forensics
Dongdong Fu;Yun Q. Shi;Wei Su.
conference on security steganography and watermarking of multimedia contents (2007)
JPEG image steganalysis utilizing both intrablock and interblock correlations
Chunhua Chen;Y.Q. Shi.
international symposium on circuits and systems (2008)
Distance-reciprocal distortion measure for binary document images
Haiping Lu;A.C. Kot;Y.Q. Shi.
IEEE Signal Processing Letters (2004)
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