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2020 – today
- 2020
[j23]Xiaofeng Zhu
, Chong-Yaw Wee, Minjeong Kim:
Deep understanding of big multimedia data. Neural Comput. Appl. 32(11): 6417-6419 (2020)- [j22]Yang Li, Jingyu Liu, Zi-Wen Peng, Can Sheng, Minjeong Kim, Pew-Thian Yap, Chong-Yaw Wee, Dinggang Shen:
Fusion of ULS Group Constrained High- and Low-Order Sparse Functional Connectivity Networks for MCI Classification. Neuroinformatics 18(1): 1-24 (2020)
2010 – 2019
- 2019
- [j21]Yang Li, Jingyu Liu, Xinqiang Gao, Biao Jie, Minjeong Kim, Pew-Thian Yap, Chong-Yaw Wee, Dinggang Shen:
Multimodal hyper-connectivity of functional networks using functionally-weighted LASSO for MCI classification. Medical Image Anal. 52: 80-96 (2019) - [j20]Yang Li, Hao Yang, Baiying Lei, Jingyu Liu, Chong-Yaw Wee:
Novel Effective Connectivity Inference Using Ultra-Group Constrained Orthogonal Forward Regression and Elastic Multilayer Perceptron Classifier for MCI Identification. IEEE Trans. Medical Imaging 38(5): 1227-1239 (2019) - [c27]Yiqiao Jiang, Huifang Huang, Jingyu Liu, Chong-Yaw Wee, Yang Li:
Adaptive Functional Connectivity Network Using Parallel Hierarchical BiLSTM for MCI Diagnosis. MLMI@MICCAI 2019: 507-515 - 2018
- [j19]Kim-Han Thung, Chong-Yaw Wee:
A brief review on multi-task learning. Multim. Tools Appl. 77(22): 29705-29725 (2018) - 2017
- [c26]Yang Li, Jingyu Liu, Mei-Lin Luo, Ke Li, Pew-Thian Yap, Minjeong Kim, Chong-Yaw Wee, Dinggang Shen:
Structural Connectivity Guided Sparse Effective Connectivity for MCI Identification. MLMI@MICCAI 2017: 299-306 - [c25]Yang Li, Jingyu Liu, Ke Li, Pew-Thian Yap, Minjeong Kim, Chong-Yaw Wee, Dinggang Shen:
Fusion of High-Order and Low-Order Effective Connectivity Networks for MCI Classification. MLMI@MICCAI 2017: 307-315 - [c24]Yang Li, Hao Yang, Ke Li, Pew-Thian Yap, Minjeong Kim, Chong-Yaw Wee, Dinggang Shen:
Novel Effective Connectivity Network Inference for MCI Identification. MLMI@MICCAI 2017: 316-324 - [c23]Yang Li, Xinqiang Gao, Biao Jie, Pew-Thian Yap, Minjeong Kim, Chong-Yaw Wee, Dinggang Shen:
Multimodal Hyper-connectivity Networks for MCI Classification. MICCAI (1) 2017: 433-441 - 2016
- [j18]Biao Jie, Chong-Yaw Wee, Dinggang Shen, Daoqiang Zhang:
Hyper-connectivity of functional networks for brain disease diagnosis. Medical Image Anal. 32: 84-100 (2016) - [j17]Heung-Il Suk, Chong-Yaw Wee, Seong-Whan Lee, Dinggang Shen:
State-space model with deep learning for functional dynamics estimation in resting-state fMRI. NeuroImage 129: 292-307 (2016) - [j16]Ehsan Adeli, Feng Shi, Le An, Chong-Yaw Wee, Guorong Wu, Tao Wang, Dinggang Shen:
Joint feature-sample selection and robust diagnosis of Parkinson's disease from MRI data. NeuroImage 141: 206-219 (2016) - 2015
- [j15]Brent C. Munsell, Chong-Yaw Wee, Simon S. Keller, Bernd Weber, Christian Erich Elger, Laura Angelica Tomaz da Silva, Travis Nesland, Martin Styner, Dinggang Shen, Leonardo Bonilha:
Evaluation of machine learning algorithms for treatment outcome prediction in patients with epilepsy based on structural connectome data. NeuroImage 118: 219-230 (2015) - [j14]Heung-Il Suk, Chong-Yaw Wee, Seong-Whan Lee, Dinggang Shen:
Supervised Discriminative Group Sparse Representation for Mild Cognitive Impairment Diagnosis. Neuroinformatics 13(3): 277-295 (2015) - [c22]Geng Chen, Pei Zhang, Ke Li, Chong-Yaw Wee, Yafeng Wu, Dinggang Shen, Pew-Thian Yap:
Block-Based Statistics for Robust Non-parametric Morphometry. Patch-MI@MICCAI 2015: 62-70 - [c21]Yue Gao, Chong-Yaw Wee, Minjeong Kim, Panteleimon Giannakopoulos, Marie-Louise Montandon, Sven Haller, Dinggang Shen:
MCI Identification by Joint Learning on Multiple MRI Data. MICCAI (2) 2015: 78-85 - [c20]Ehsan Adeli-Mosabbeb, Chong-Yaw Wee, Le An, Feng Shi, Dinggang Shen:
Joint Feature-Sample Selection and Robust Classification for Parkinson's Disease Diagnosis. MCV@MICCAI 2015: 127-136 - [c19]Yan Jin, Chong-Yaw Wee, Feng Shi, Kim-Han Thung, Pew-Thian Yap, Dinggang Shen:
Identification of Infants at Risk for Autism Using Multi-parameter Hierarchical White Matter Connectomes. MLMI 2015: 170-177 - 2014
- [j13]Feng Liu, Chong-Yaw Wee, Huafu Chen, Dinggang Shen:
Inter-modality relationship constrained multi-modality multi-task feature selection for Alzheimer's Disease and mild cognitive impairment identification. NeuroImage 84: 466-475 (2014) - [j12]Kim-Han Thung, Chong-Yaw Wee, Pew-Thian Yap, Dinggang Shen:
Neurodegenerative disease diagnosis using incomplete multi-modality data via matrix shrinkage and completion. NeuroImage 91: 386-400 (2014) - [j11]Yang Li, Chong-Yaw Wee, Biao Jie, Zi-Wen Peng, Dinggang Shen:
Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification. Neuroinformatics 12(3): 455-469 (2014) - [j10]Biao Jie, Daoqiang Zhang, Wei Gao, Qian Wang, Chong-Yaw Wee, Dinggang Shen:
Integration of Network Topological and Connectivity Properties for Neuroimaging Classification. IEEE Trans. Biomed. Eng. 61(2): 576-589 (2014) - [c18]True Price, Chong-Yaw Wee, Wei Gao, Dinggang Shen:
Multiple-Network Classification of Childhood Autism Using Functional Connectivity Dynamics. MICCAI (3) 2014: 177-184 - [p1]Dinggang Shen, Chong-Yaw Wee, Daoqiang Zhang, Luping Zhou, Pew-Thian Yap:
Machine Learning Techniques for AD/MCI Diagnosis and Prognosis. Machine Learning in Healthcare Informatics 2014: 147-179 - 2013
- [c17]Biao Jie, Daoqiang Zhang, Heung-Il Suk, Chong-Yaw Wee, Dinggang Shen:
Integrating Multiple Network Properties for MCI Identification. MLMI 2013: 9-16 - [c16]Heung-Il Suk, Chong-Yaw Wee, Dinggang Shen:
Discriminative Group Sparse Representation for Mild Cognitive Impairment Classification. MLMI 2013: 131-138 - [c15]Chong-Yaw Wee, Sen Yang, Pew-Thian Yap, Dinggang Shen:
Temporally Dynamic Resting-State Functional Connectivity Networks for Early MCI Identification. MLMI 2013: 139-146 - [c14]Kim-Han Thung, Chong-Yaw Wee, Pew-Thian Yap, Dinggang Shen:
Identification of Alzheimer's Disease Using Incomplete Multimodal Dataset via Matrix Shrinkage and Completion. MLMI 2013: 163-170 - [c13]Pei Zhang, Chong-Yaw Wee, Marc Niethammer, Dinggang Shen, Pew-Thian Yap:
Large Deformation Image Classification Using Generalized Locality-Constrained Linear Coding. MICCAI (1) 2013: 292-299 - [c12]Feng Liu, Chong-Yaw Wee, Huafu Chen, Dinggang Shen:
Inter-modality Relationship Constrained Multi-Task Feature Selection for AD/MCI Classification. MICCAI (1) 2013: 308-315 - [c11]Feng Liu, Heung-Il Suk, Chong-Yaw Wee, Huafu Chen, Dinggang Shen:
High-Order Graph Matching Based Feature Selection for Alzheimer's Disease Identification. MICCAI (2) 2013: 311-318 - [c10]Chong-Yaw Wee, Yang Li, Biao Jie, Zi-Wen Peng, Dinggang Shen:
Identification of MCI Using Optimal Sparse MAR Modeled Effective Connectivity Networks. MICCAI (2) 2013: 319-327 - 2012
- [j9]Chong-Yaw Wee, Pew-Thian Yap, Daoqiang Zhang, Kevin Denny, Jeffrey N. Browndyke, Guy G. Potter, Kathleen Welsh-Bohmer, Lihong Wang, Dinggang Shen:
Identification of MCI individuals using structural and functional connectivity networks. NeuroImage 59(3): 2045-2056 (2012) - [c9]Biao Jie, Daoqiang Zhang, Chong-Yaw Wee, Dinggang Shen:
Structural Feature Selection for Connectivity Network-Based MCI Diagnosis. MBIA 2012: 175-184 - [c8]Yaping Wang, Hongjun Jia, Pew-Thian Yap, Bo Cheng, Chong-Yaw Wee, Lei Guo, Dinggang Shen:
Groupwise Segmentation Improves Neuroimaging Classification Accuracy. MBIA 2012: 185-193 - [c7]Chong-Yaw Wee, Pew-Thian Yap, Daoqiang Zhang, Lihong Wang, Dinggang Shen:
Constrained Sparse Functional Connectivity Networks for MCI Classification. MICCAI (2) 2012: 212-219 - 2011
- [j8]Chong-Yaw Wee, Pew-Thian Yap, Wenbin Li, Kevin Denny, Jeffrey N. Browndyke, Guy G. Potter, Kathleen Welsh-Bohmer, Lihong Wang, Dinggang Shen:
Enriched white matter connectivity networks for accurate identification of MCI patients. NeuroImage 54(3): 1812-1822 (2011) - [c6]Chong-Yaw Wee, Pew-Thian Yap, Daoqiang Zhang, Kevin Denny, Lihong Wang, Dinggang Shen:
Identification of Individuals with MCI via Multimodality Connectivity Networks. MICCAI (2) 2011: 277-284 - 2010
- [j7]Chong-Yaw Wee, Paramesran Raveendran, Ramakrishnan Mukundan, Xudong Jiang:
Image quality assessment by discrete orthogonal moments. Pattern Recognit. 43(12): 4055-4068 (2010) - [c5]Chong-Yaw Wee, Pew-Thian Yap, Jeffery N. Browndyke, Guy G. Potter, David C. Steffens, Kathleen Welsh-Bohmer, Lihong Wang, Dinggang Shen:
Accurate Identification of MCI Patients via Enriched White-Matter Connectivity Network. MLMI 2010: 140-147
2000 – 2009
- 2009
- [j6]Chong-Yaw Wee, Paramesran Raveendran, Fumiaki Takeda:
Sorting of rice grains using Zernike moments. J. Real Time Image Process. 4(4): 353-363 (2009) - 2008
- [j5]Chong-Yaw Wee, Paramesran Raveendran, R. Mukundan:
Fast computation of geometric moments using a symmetric kernel. Pattern Recognit. 41(7): 2369-2380 (2008) - 2007
- [j4]Chong-Yaw Wee, Paramesran Raveendran:
Measure of image sharpness using eigenvalues. Inf. Sci. 177(12): 2533-2552 (2007) - [j3]Chong-Yaw Wee, Paramesran Raveendran:
On the computational aspects of Zernike moments. Image Vis. Comput. 25(6): 967-980 (2007) - [c4]Chong-Yaw Wee, Paramesran Raveendran, R. Mukundan:
Quality Assessment of Gaussian Blurred Images Using Symmetric Geometric Moments. ICIAP 2007: 807-812 - [c3]Chong-Yaw Wee, Paramesran Raveendran, Fumiaki Takeda:
Fast Computation of Zernike Moments For Rice Sorting System. ICIP (6) 2007: 165-168 - 2006
- [j2]Chong-Yaw Wee, Paramesran Raveendran:
Efficient computation of radial moment functions using symmetrical property. Pattern Recognit. 39(11): 2036-2046 (2006) - 2004
- [j1]Chong-Yaw Wee, Paramesran Raveendran, Fumiaki Takeda:
New computational methods for full and subset Zernike moments. Inf. Sci. 159(2): 203-220 (2004) - 2002
- [c2]Chong-Yaw Wee, Raveendran Paramesran, Fumiaki Takeda, Takeo Tsuzuki, Hiroshi Kadota, Satoshi Shimanouchi:
Classification of rice grains using fuzzy artmap neural network. APCCAS (2) 2002: 223-226 - [c1]Chong-Yaw Wee, Paramesran Raveendran, Fumiaki Takeda, Takeo Tsuzuki, Hiroshi Kadota, Satoshi Shimanouchi:
Classification of Rice Grain Using New Scale Invariant Zernike Moments. JCIS 2002: 832-835
Coauthor Index
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