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ORCIDQiang Shawn Cheng
Qiang Cheng 0001
Person information
- affiliation: University of Kentucky, Department of Computer Science, Institute of Biomedical Informatics, Lexington, KY, USA
- affiliation (2012 - 2017): Southern Illinois University, Department of Computer Science, Carbondale, IL, USA
- affiliation: Siemens Medical Solutions, Inc., Princeton, NJ, USA
- affiliation (PhD 2002): University of Illinois, Urbana-Champaign, IL, USA
Other persons with the same name
- Qiang Cheng — disambiguation page
- Qiang Cheng 0002
![[0000-0002-2442-8357]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-2442-8357")
— Southeast University, State Key Laboratory of Millimeter Waves, Nanjing, China - Qiang Cheng 0003 — China Agricultural University, College of Information and Electrical Engineering, Beijing, China
- Qiang Cheng 0004 — Beijing University of Technology, College of Mechanical Engineering and Applied Electronics Technology, Institute of Advanced Manufacturing and Intelligent Technology, Beijing, China (and 1 more)
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2020 – today
- 2024
[j38]Aram Ansary Ogholbake, Qiang Cheng:
Gene expression clock: an unsupervised deep learning approach for predicting circadian rhythmicity from whole genome expression. Neural Comput. Appl. 36(33): 20653-20670 (2024)- [j37]Chong Peng, Kehan Kang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Fine-Grained Essential Tensor Learning for Robust Multi-View Spectral Clustering. IEEE Trans. Image Process. 33: 3145-3160 (2024) - [j36]Honglei Su, Qi Liu, Hui Yuan, Qiang Cheng, Raouf Hamzaoui:
Support Vector Regression-Based Reduced- Reference Perceptual Quality Model for Compressed Point Clouds. IEEE Trans. Multim. 26: 6238-6249 (2024) - [c53]Chong Peng, Pengfei Zhang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Shawn Cheng:
Fine-Grained Bipartite Concept Factorization for Clustering. CVPR 2024: 26254-26264 - [c52]Md Atik Ahamed, Qiang Shawn Cheng:
TimeMachine: A Time Series is Worth 4 Mambas for Long-Term Forecasting. ECAI 2024: 1688-1695 - [c51]Chong Peng, Kai Zhang, Yongyong Chen, Chenglizhao Chen, Qiang Cheng:
Cross-View Diversity Embedded Consensus Learning for Multi-View Clustering. IJCAI 2024: 4788-4796 - [c50]Md Atik Ahamed, Qiang Shawn Cheng:
MambaTab: A Plug-and-Play Model for Learning Tabular Data. MIPR 2024: 369-375 - [i32]Md Atik Ahamed, Qiang Cheng:
MambaTab: A Simple Yet Effective Approach for Handling Tabular Data. CoRR abs/2401.08867 (2024) - [i31]Md Atik Ahamed, Qiang Cheng:
TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting. CoRR abs/2403.09898 (2024) - [i30]Md Atik Ahamed, Qiang Cheng:
TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification. CoRR abs/2406.04419 (2024) - 2023
- [j35]Chong Peng, Xingrong Hou, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Global and local similarity learning in multi-kernel space for nonnegative matrix factorization. Knowl. Based Syst. 279: 110946 (2023) - [e1]Reyer Zwiggelaar, Geetha Ganesan, Qiang Shawn Cheng, Ke-Lin Du, Srinivasa Rao Satti:
Proceedings of the Algorithms, Computing and Mathematics Conference 2022 (ACM 2022), Hybrid Event, Chennai, India, August 29 - 30, 2022. CEUR Workshop Proceedings 3445, CEUR-WS.org 2023 [contents] - 2022
- [j34]Chong Peng, Zhilu Zhang, Chenglizhao Chen, Zhao Kang, Qiang Cheng:
Two-dimensional semi-nonnegative matrix factorization for clustering. Inf. Sci. 590: 106-141 (2022) - [j33]Chong Peng, Yiqun Zhang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Log-based sparse nonnegative matrix factorization for data representation. Knowl. Based Syst. 251: 109127 (2022) - [j32]Chong Peng, Jing Zhang, Yongyong Chen, Xin Xing, Chenglizhao Chen, Zhao Kang, Li Guo, Qiang Cheng:
Preserving bilateral view structural information for subspace clustering. Knowl. Based Syst. 258: 109915 (2022) - [j31]Chong Peng, Yang Liu, Kehan Kang, Yongyong Chen, Xinxing Wu, Andrew Cheng, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Hyperspectral Image Denoising Using Nonconvex Local Low-Rank and Sparse Separation With Spatial-Spectral Total Variation Regularization. IEEE Trans. Geosci. Remote. Sens. 60: 1-17 (2022) - [c49]Xinxing Wu, Qiang Cheng:
Stabilizing and Enhancing Link Prediction through Deepened Graph Auto-Encoders. IJCAI 2022: 3587-3593 - [i29]Chong Peng, Yang Liu, Yongyong Chen, Xinxin Wu, Andrew Cheng, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Hyperspectral Image Denoising Using Non-convex Local Low-rank and Sparse Separation with Spatial-Spectral Total Variation Regularization. CoRR abs/2201.02812 (2022) - [i28]Chong Peng, Yiqun Zhang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Log-based Sparse Nonnegative Matrix Factorization for Data Representation. CoRR abs/2204.10647 (2022) - [i27]Xinxing Wu, Chong Peng, Gregory Jicha, Donna Wilcock, Qiang Cheng:
PRIME: Uncovering Circadian Oscillation Patterns and Associations with AD in Untimed Genome-wide Gene Expression across Multiple Brain Regions. CoRR abs/2208.12811 (2022) - [i26]Xinxing Wu, Chong Peng, Peter T. Nelson, Qiang Cheng:
Alcohol Intake Differentiates AD and LATE: A Telltale Lifestyle from Two Large-Scale Datasets. CoRR abs/2209.05438 (2022) - [i25]Xinxing Wu, Chong Peng, Richard J. Charnigo, Qiang Cheng:
Explainable Censored Learning: Finding Critical Features with Long Term Prognostic Values for Survival Prediction. CoRR abs/2209.15450 (2022) - 2021
- [j30]Xinghua Yao, Xiaojin Li, Qiang Ye, Yan Huang, Qiang Cheng, Guo-Qiang Zhang:
A robust deep learning approach for automatic classification of seizures against non-seizures. Biomed. Signal Process. Control. 64: 102215 (2021) - [j29]Chong Peng, Zhilu Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Nonnegative matrix factorization with local similarity learning. Inf. Sci. 562: 325-346 (2021) - [j28]Chong Peng, Yang Liu, Xin Zhang, Zhao Kang, Yongyong Chen, Chenglizhao Chen, Qiang Cheng:
Learning discriminative representation for image classification. Knowl. Based Syst. 233: 107517 (2021) - [j27]Zhao Kang, Chong Peng, Qiang Cheng, Xinwang Liu, Xi Peng, Zenglin Xu, Ling Tian:
Structured graph learning for clustering and semi-supervised classification. Pattern Recognit. 110: 107627 (2021) - [j26]Chong Peng, Qian Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Kernel two-dimensional ridge regression for subspace clustering. Pattern Recognit. 113: 107749 (2021) - [j25]Chong Peng, Qiang Cheng:
Discriminative Ridge Machine: A Classifier for High-Dimensional Data or Imbalanced Data. IEEE Trans. Neural Networks Learn. Syst. 32(6): 2595-2609 (2021) - [c48]Xinxing Wu, Qiang Cheng:
Fractal Autoencoders for Feature Selection. AAAI 2021: 10370-10378 - [c47]Vasily Zadorozhnyy, Qiang Cheng, Qiang Ye:
Adaptive Weighted Discriminator for Training Generative Adversarial Networks. CVPR 2021: 4781-4790 - [c46]Yang Liu, Qian Zhang, Yongyong Chen, Qiang Cheng, Chong Peng:
Hyperspectral Image Denoising With Log-Based Robust PCA. ICIP 2021: 1634-1638 - [c45]Xinxing Wu, Qiang Cheng:
Algorithmic stability and generalization of an unsupervised feature selection algorithm. NeurIPS 2021: 19860-19875 - [i24]Xinxing Wu, Qiang Cheng:
Deepened Graph Auto-Encoders Help Stabilize and Enhance Link Prediction. CoRR abs/2103.11414 (2021) - [i23]Yang Liu, Qian Zhang, Yongyong Chen, Qiang Cheng, Chong Peng:
Hyperspectral Image Denoising with Log-Based Robust PCA. CoRR abs/2105.11927 (2021) - 2020
- [j24]Chong Peng, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Robust principal component analysis: A factorization-based approach with linear complexity. Inf. Sci. 513: 581-599 (2020) - [i22]Chong Peng, Zhilu Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Two-Dimensional Semi-Nonnegative Matrix Factorization for Clustering. CoRR abs/2005.09229 (2020) - [i21]Zhao Kang, Chong Peng, Qiang Cheng, Xinwang Liu, Xi Peng, Zenglin Xu, Ling Tian:
Structured Graph Learning for Clustering and Semi-supervised Classification. CoRR abs/2008.13429 (2020) - [i20]Xinxing Wu, Qiang Cheng:
A Uniformly Stable Algorithm For Unsupervised Feature Selection. CoRR abs/2010.09416 (2020) - [i19]Xinxing Wu, Qiang Cheng:
Fractal Autoencoders for Feature Selection. CoRR abs/2010.09430 (2020) - [i18]Chong Peng, Qian Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Kernel Two-Dimensional Ridge Regression for Subspace Clustering. CoRR abs/2011.01477 (2020) - [i17]Vasily Zadorozhnyy, Qiang Cheng, Qiang Ye:
Adaptive Weighted Discriminator for Training Generative Adversarial Networks. CoRR abs/2012.03149 (2020)
2010 – 2019
- 2019
- [c44]Chong Peng, Chenglizhao Chen, Zhao Kang, Jianbo Li, Qiang Cheng:
RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices. CVPR 2019: 7317-7325 - [c43]Liyu Gong, Qiang Cheng:
Exploiting Edge Features for Graph Neural Networks. CVPR 2019: 9211-9219 - [i16]Liyu Gong, Qiang Cheng:
Lie Group Auto-Encoder. CoRR abs/1901.09970 (2019) - [i15]Xinghua Yao, Qiang Cheng, Guo-Qiang Zhang:
A Novel Independent RNN Approach to Classification of Seizures against Non-seizures. CoRR abs/1903.09326 (2019) - [i14]Chong Peng, Qiang Cheng:
Discriminative Regression Machine: A Classifier for High-Dimensional Data or Imbalanced Data. CoRR abs/1904.07496 (2019) - [i13]Chong Peng, Chenglizhao Chen, Zhao Kang, Jianbo Li, Qiang Cheng:
RES-PCA: A Scalable Approach to Recovering Low-rank Matrices. CoRR abs/1904.07497 (2019) - [i12]Xinghua Yao, Qiang Cheng, Guo-Qiang Zhang:
Automated Classification of Seizures against Nonseizures: A Deep Learning Approach. CoRR abs/1906.02745 (2019) - [i11]Chong Peng, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Nonnegative Matrix Factorization with Local Similarity Learning. CoRR abs/1907.04150 (2019) - 2018
- [j23]Chong Peng, Zhao Kang, Shuting Cai, Qiang Cheng:
Integrate and Conquer: Double-Sided Two-Dimensional k-Means Via Integrating of Projection and Manifold Construction. ACM Trans. Intell. Syst. Technol. 9(5): 57:1-57:25 (2018) - [c42]Zhao Kang, Chong Peng, Qiang Cheng, Zenglin Xu:
Unified Spectral Clustering With Optimal Graph. AAAI 2018: 3366-3373 - [i10]Xinghua Yao, Xiaojin Li, Qiang Ye, Yan Huang, Qiang Cheng, Guoqiang Zhang:
A Robust Deep Learning Approach for Automatic Seizure Detection. CoRR abs/1812.06562 (2018) - 2017
- [j22]Chong Peng, Zhao Kang, Qiang Cheng:
Integrating feature and graph learning with low-rank representation. Neurocomputing 249: 106-116 (2017) - [j21]Zhao Kang, Chong Peng, Qiang Cheng:
Kernel-driven similarity learning. Neurocomputing 267: 210-219 (2017) - [j20]Chong Peng, Zhao Kang, Fei Xu, Yongyong Chen, Qiang Cheng:
Image Projection Ridge Regression for Subspace Clustering. IEEE Signal Process. Lett. 24(7): 991-995 (2017) - [j19]Chong Peng, Jie Cheng, Qiang Cheng:
A Supervised Learning Model for High-Dimensional and Large-Scale Data. ACM Trans. Intell. Syst. Technol. 8(2): 30:1-30:23 (2017) - [j18]Chong Peng, Zhao Kang, Yunhong Hu, Jie Cheng, Qiang Cheng:
Nonnegative Matrix Factorization with Integrated Graph and Feature Learning. ACM Trans. Intell. Syst. Technol. 8(3): 42:1-42:29 (2017) - [j17]Chong Peng, Zhao Kang, Yunhong Hu, Jie Cheng, Qiang Cheng:
Robust Graph Regularized Nonnegative Matrix Factorization for Clustering. ACM Trans. Knowl. Discov. Data 11(3): 33:1-33:30 (2017) - [c41]Zhao Kang, Chong Peng, Qiang Cheng:
Twin Learning for Similarity and Clustering: A Unified Kernel Approach. AAAI 2017: 2080-2086 - [c40]Chong Peng, Zhao Kang, Qiang Cheng:
Subspace Clustering via Variance Regularized Ridge Regression. CVPR 2017: 682-691 - [c39]Zhao Kang, Chong Peng, Ming Yang, Qiang Cheng:
Exploiting Nonlinear Relationships for Top-N Recommender Systems. ICBK 2017: 49-56 - [c38]Zhao Kang, Chong Peng, Qiang Cheng:
Clustering with Adaptive Manifold Structure Learning. ICDE 2017: 79-82 - [i9]Zhao Kang, Chong Peng, Qiang Cheng:
Twin Learning for Similarity and Clustering: A Unified Kernel Approach. CoRR abs/1705.00678 (2017) - [i8]Zhao Kang, Chong Peng, Qiang Cheng, Zenglin Xu:
Unified Spectral Clustering with Optimal Graph. CoRR abs/1711.04258 (2017) - 2016
- [j16]Chong Peng, Zhao Kang, Ming Yang, Qiang Cheng:
Feature Selection Embedded Subspace Clustering. IEEE Signal Process. Lett. 23(7): 1018-1022 (2016) - [c37]Zhao Kang, Chong Peng, Qiang Cheng:
Top-N Recommender System via Matrix Completion. AAAI 2016: 179-185 - [c36]Zhao Kang, Chong Peng, Ming Yang, Qiang Cheng:
Top-N Recommendation on Graphs. CIKM 2016: 2101-2106 - [c35]Chong Peng, Zhao Kang, Ming Yang, Qiang Cheng:
RAP: Scalable RPCA for Low-rank Matrix Recovery. CIKM 2016: 2113-2118 - [c34]Chong Peng, Zhao Kang, Qiang Cheng:
A Fast Factorization-Based Approach to Robust PCA. ICDM 2016: 1137-1142 - [c33]Zhao Kang, Qiang Cheng:
Top-N Recommendation with Novel Rank Approximation. SDM 2016: 126-134 - [i7]Zhao Kang, Chong Peng, Qiang Cheng:
Top-N Recommender System via Matrix Completion. CoRR abs/1601.04800 (2016) - [i6]Zhao Kang, Qiang Cheng:
Top-N Recommendation with Novel Rank Approximation. CoRR abs/1602.07783 (2016) - [i5]Zhao Kang, Chong Peng, Ming Yang, Qiang Cheng:
Top-N Recommendation on Graphs. CoRR abs/1609.08264 (2016) - 2015
- [j15]Zhao Kang, Chong Peng, Jie Cheng, Qiang Cheng:
LogDet Rank Minimization with Application to Subspace Clustering. Comput. Intell. Neurosci. 2015: 824289:1-824289:10 (2015) - [j14]Zhao Kang, Chong Peng, Qiang Cheng:
Robust Subspace Clustering via Smoothed Rank Approximation. IEEE Signal Process. Lett. 22(11): 2088-2092 (2015) - [j13]Hongbo Zhou, Qiang Cheng:
A Scalable Projective Scaling Algorithm for lp Loss With Convex Penalizations. IEEE Trans. Neural Networks Learn. Syst. 26(2): 265-276 (2015) - [c32]Zhao Kang, Chong Peng, Qiang Cheng:
Robust Subspace Clustering via Tighter Rank Approximation. CIKM 2015: 393-401 - [c31]Zhao Kang, Chong Peng, Qiang Cheng:
Robust PCA Via Nonconvex Rank Approximation. ICDM 2015: 211-220 - [c30]Chong Peng, Zhao Kang, Huiqing Li, Qiang Cheng:
Subspace Clustering Using Log-determinant Rank Approximation. KDD 2015: 925-934 - [i4]Zhao Kang, Chong Peng, Jie Cheng, Qiang Cheng:
LogDet Rank Minimization with Application to Subspace Clustering. CoRR abs/1507.00908 (2015) - [i3]Zhao Kang, Chong Peng, Qiang Cheng:
Robust Subspace Clustering via Smoothed Rank Approximation. CoRR abs/1508.04467 (2015) - [i2]Zhao Kang, Chong Peng, Qiang Cheng:
Robust Subspace Clustering via Tighter Rank Approximation. CoRR abs/1510.08971 (2015) - [i1]Zhao Kang, Chong Peng, Qiang Cheng:
Robust PCA via Nonconvex Rank Approximation. CoRR abs/1511.05261 (2015) - 2014
- [j12]Qiang Cheng, Hongbo Zhou, Jie Cheng, Huiqing Li:
A Minimax Framework for Classification with Applications to Images and High Dimensional Data. IEEE Trans. Pattern Anal. Mach. Intell. 36(11): 2117-2130 (2014) - [j11]Qiang Cheng, Jale Tezcan, Jie Cheng:
Confidence and prediction intervals for semiparametric mixed-effect least squares support vector machine. Pattern Recognit. Lett. 40: 88-95 (2014) - 2013
- [c29]Yang Bai, Jale Tezcan, Qiang Cheng, Jie Cheng:
A Multiway Model for Predicting Earthquake Ground Motion. SNPD 2013: 219-224 - 2011
- [j10]Qiang Cheng, Hongbo Zhou, Jie Cheng:
The Fisher-Markov Selector: Fast Selecting Maximally Separable Feature Subset for Multiclass Classification with Applications to High-Dimensional Data. IEEE Trans. Pattern Anal. Mach. Intell. 33(6): 1217-1233 (2011) - [j9]Jie Cheng, Mohammad R. Sayeh, Mehdi R. Zargham, Qiang Cheng:
Real-Time Vector Quantization and Clustering Based on Ordinary Differential Equations. IEEE Trans. Neural Networks 22(12): 2143-2148 (2011) - [c28]Hongbo Zhou, Qiang Cheng:
O(N) implicit subspace embedding for unsupervised multi-scale image segmentation. CVPR 2011: 2209-2215 - 2010
- [j8]Qiang Cheng:
A Sparse Learning Machine for High-Dimensional Data with Application to Microarray Gene Analysis. IEEE ACM Trans. Comput. Biol. Bioinform. 7(4): 636-646 (2010) - [c27]Hongbo Zhou, Qiang Cheng:
Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework. NIPS 2010: 2577-2585 - [c26]Hongbo Zhou, Qiang Cheng, Zhikun She:
Reparameterization based consistent graph-structured linear programs. SAC 2010: 974-978 - [c25]Hongbo Zhou, Qiang Cheng, Hong-Ju Yang, Haiyun Xu:
Weighted Kernel Density Estimation of the Prepulse Inhibition Test. SERVICES 2010: 291-297
2000 – 2009
- 2009
- [j7]Qiang Cheng, Jie Cheng:
Sparsity Optimization Method for Multivariate Feature Screening for Gene Expression Analysis. J. Comput. Biol. 16(9): 1241-1252 (2009) - [j6]Qiang Cheng:
Generalized Embedding of Multiplicative Watermarks. IEEE Trans. Circuits Syst. Video Technol. 19(7): 978-988 (2009) - [c24]Ning Yu, Kyu Hong Cho, Qiang Cheng, Rafael A. Tesorero:
A Hybrid Computational Approach for the Prediction of Small Non-coding RNAs from Genome Sequences. CSE (2) 2009: 1071-1076 - [c23]Hongbo Zhou, Hong-Ju Yang, Haiyun Xu, Qiang Cheng:
A New Computational Tool for the Post Session Analysis of the Prepulse Inhibition Test in Neural Science. CSE (2) 2009: 1077-1080 - [c22]Huyu Qu, Jie Cheng, Qiang Cheng, Le Yi Wang:
WiFi-Based Telemedicine System: Signal Accuracy and Security. CSE (2) 2009: 1081-1085 - [c21]Hongbo Zhou, Qiang Cheng, Mehdi R. Zargham:
Fast Fusion of Medical Images Based on Bayesian Risk Minimization and Pixon Map. CSE (2) 2009: 1086-1091 - 2008
- [j5]Qiang Shawn Cheng, Mehdi R. Zargham:
Efficient compression for multiplanar reformulated biomedical images for interactive visualisation. Int. J. Funct. Informatics Pers. Medicine 1(1): 68-79 (2008) - [j4]Liqiang Zhang, Qiang Cheng, Yingge Wang, Sherali Zeadally:
A Novel Distributed Sensor Positioning System Using the Dual of Target Tracking. IEEE Trans. Computers 57(2): 246-260 (2008) - [c20]Hongbo Zhou, Qiang Shawn Cheng, Mehdi R. Zargham:
Prediction of Protein Function Using Graph Container and Message Passing. BIOCOMP 2008: 718-723 - 2007
- [c19]Qiang Shawn Cheng, Mehdi R. Zargham:
An Efficient Compression Method for Multiplanar Reformulated Biomedical Images. BIBE 2007: 578-584 - 2006
- [c18]Liqiang Zhang, Xiaobo Zhou, Qiang Cheng:
Landscape-3D; A Robust Localization Scheme for Sensor Networks over Complex 3D Terrains. LCN 2006: 239-246 - 2005
- [c17]Yingge Wang, Qiang Cheng, Jie Cheng:
SNR Analysis for Phased-Array MRI. ICASSP (2) 2005: 493-496 - [c16]Huyu Qu, Qiang Cheng, Ece Yaprak:
Using Covert Channel to Resist DoS attacks in WLAN. ICWN 2005: 38-44 - [c15]Liqiang Zhang, Qiang Cheng, Yingge Wang, Sherali Zeadally:
Landscape: a high performance distributed positioning scheme for outdoor sensor networks. WiMob (3) 2005: 430-437 - 2004
- [j3]Qiang Cheng, Yingge Wang, Thomas S. Huang:
Performance analysis and error exponents of asymmetric watermarking systems. Signal Process. 84(8): 1429-1445 (2004) - [c14]Xuanwen Luo, Qiang Cheng:
Unconfined mobile Bluetooth nursing and daily data collection. CCNC 2004: 693-696 - [c13]Yingge Wang, Qiang Cheng, Jie Cheng, Thomas S. Huang:
MV-MAP: Multiresolution Video Visualization and Summarization on MAPs. ICPR (3) 2004: 886-889 - 2003
- [j2]Qiang Cheng, Thomas S. Huang:
Robust optimum detection of transform domain multiplicative watermarks. IEEE Trans. Signal Process. 51(4): 906-924 (2003) - [c12]Qiang Cheng, Yingge Wang, Thomas S. Huang:
How to design efficient watermarks? ICASSP (3) 2003: 49-52 - [c11]Qiang Cheng, Yingge Wang, Thomas S. Huang:
Maximizing efficacy for efficient watermarking systems. ICIP (2) 2003: 747-750 - 2002
- [b1]Qiang Cheng:
Multimedia Watermarking. University of Illinois Urbana-Champaign, USA, 2002 - [c10]Qiang Cheng, Thomas S. Huang:
Optimum detection and decoding of multiplicative watermarks in DFT domain. ICASSP 2002: 3477-3480 - [c9]Qiang Cheng, Ruoyu Roy Wang, Thomas S. Huang:
Framework for digital video watermarking with dual watermarks. VCIP 2002: 513-520 - 2001
- [j1]Qiang Cheng, Thomas S. Huang:
An additive approach to transform-domain information hiding and optimum detection structure. IEEE Trans. Multim. 3(3): 273-284 (2001) - [c8]