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2020 – today
- 2025
[j49]Kwanseok Oh
, Da-Woon Heo, Ahmad Wisnu Mulyadi, Wonsik Jung, Eunsong Kang, Kun Ho Lee, Heung-Il Suk:
A quantitatively interpretable model for Alzheimer's disease prediction using deep counterfactuals. NeuroImage 309: 121077 (2025)- 2024
- [j48]Seungwoo Jeong, Wonjun Ko, Ahmad Wisnu Mulyadi, Heung-Il Suk:
Deep Efficient Continuous Manifold Learning for Time Series Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 46(1): 171-184 (2024) - [j47]Jee Seok Yoon, Kwanseok Oh, Yooseung Shin, Maciej A. Mazurowski, Heung-Il Suk:
Domain Generalization for Medical Image Analysis: A Review. Proc. IEEE 112(10): 1583-1609 (2024) - [j46]Wonjun Ko, Seungwoo Jeong, Sa-Kwang Song, Heung-Il Suk:
EEG-Oriented Self-Supervised Learning With Triple Information Pathways Network. IEEE Trans. Cybern. 54(11): 6495-6508 (2024) - [j45]Eunsong Kang, Da-Woon Heo, Jiwon Lee, Heung-Il Suk:
A Learnable Counter-Condition Analysis Framework for Functional Connectivity-Based Neurological Disorder Diagnosis. IEEE Trans. Medical Imaging 43(4): 1377-1387 (2024) - [j44]Wonsik Jung, Eunjin Jeon, Eunsong Kang, Heung-Il Suk:
EAG-RS: A Novel Explainability-Guided ROI-Selection Framework for ASD Diagnosis via Inter-Regional Relation Learning. IEEE Trans. Medical Imaging 43(4): 1400-1411 (2024) - [j43]Eunji Jun, Seungwoo Jeong, Da-Woon Heo, Heung-Il Suk:
Medical Transformer: Universal Encoder for 3-D Brain MRI Analysis. IEEE Trans. Neural Networks Learn. Syst. 35(12): 17779-17789 (2024) - [j42]Jaein Lee, Eunsong Kang, Da-Woon Heo, Heung-Il Suk:
Site-Invariant Meta-Modulation Learning for Multisite Autism Spectrum Disorders Diagnosis. IEEE Trans. Neural Networks Learn. Syst. 35(12): 18062-18075 (2024) - [c65]Sangmin Jo, Seungwoo Jeong, Jaehyun Jeon, Heung-Il Suk:
Enhancing EEG Domain Generalization via Weighted Contrastive Learning. BCI 2024: 1-4 - [c64]Jungye Kim, Seungwoo Jeong, Jaehyun Jeon, Heung-Il Suk:
Unveiling Diagnostic Potential: EEG Microstate Representation Model for Alzheimer's Disease and Frontotemporal Dementia. BCI 2024: 1-4 - [c63]Jiwon Lee, Eunsong Kang, Junyeong Maeng, Heung-Il Suk:
Eigendecomposition-Based Spatial-Temporal Attention for Brain Cognitive States Identification. ICASSP 2024: 1921-1925 - [c62]Wooyeol Park, Ahmad Wisnu Mulyadi, Eunsong Kang, Heung-Il Suk:
Prototype-Guided Contrastive Knowledge Graph Representation Learning for Diagnosis Prediction. ICPRAI (1) 2024: 262-275 - [c61]Ah-Yeong Jeong, Da-Woon Heo, Eunsong Kang, Heung-Il Suk:
BrainWaveNet: Wavelet-Based Transformer for Autism Spectrum Disorder Diagnosis. MICCAI (2) 2024: 56-66 - [i28]Kwanseok Oh, Jieun Lee, Da-Woon Heo, Dinggang Shen, Heung-Il Suk:
Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging. CoRR abs/2402.08409 (2024) - [i27]Kwanseok Oh, Eunjin Jeon, Da-Woon Heo, Yooseung Shin, Heung-Il Suk:
FIESTA: Fourier-Based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation. CoRR abs/2406.14308 (2024) - [i26]Yooseung Shin, Kwanseok Oh, Heung-Il Suk:
DyMix: Dynamic Frequency Mixup Scheduler based Unsupervised Domain Adaptation for Enhancing Alzheimer's Disease Identification. CoRR abs/2410.12827 (2024) - [i25]Junyeong Maeng, Kwanseok Oh, Wonsik Jung, Heung-Il Suk:
IdenBAT: Disentangled Representation Learning for Identity-Preserved Brain Age Transformation. CoRR abs/2410.16945 (2024) - 2023
- [j41]Ahmad Wisnu Mulyadi, Wonsik Jung, Kwanseok Oh, Jee Seok Yoon, Kun Ho Lee, Heung-Il Suk:
Estimating explainable Alzheimer's disease likelihood map via clinically-guided prototype learning. NeuroImage 273: 120073 (2023) - [j40]Kwanseok Oh, Jee Seok Yoon, Heung-Il Suk:
Learn-Explain-Reinforce: Counterfactual Reasoning and its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4843-4857 (2023) - [j39]Jaeun Phyo, Wonjun Ko, Eunjin Jeon, Heung-Il Suk:
TransSleep: Transitioning-Aware Attention-Based Deep Neural Network for Sleep Staging. IEEE Trans. Cybern. 53(7): 4500-4510 (2023) - [j38]Eunjin Jeon, Wonjun Ko, Jee Seok Yoon, Heung-Il Suk:
Mutual Information-Driven Subject-Invariant and Class-Relevant Deep Representation Learning in BCI. IEEE Trans. Neural Networks Learn. Syst. 34(2): 739-749 (2023) - [c60]Yooseung Shin, Junyeong Maeng, Kwanseok Oh, Heung-Il Suk:
Frequency Mixup Manipulation Based Unsupervised Domain Adaptation for Brain Disease Identification. ACPR (3) 2023: 123-135 - [c59]Seungwoo Jeong, Eunjin Jeon, Seungpyo Noh, Jinsool Lee, Hyungjin Kim, Seonguk Kim, Heung-Il Suk:
Learning-based Sleep Quality Evaluation. BCI 2023: 1-2 - [c58]Sangmin Jo, Jaehyun Jeon, Seungwoo Jeong, Heung-Il Suk:
Channel-Aware Self-Supervised Learning for EEG-based BCI. BCI 2023: 1-4 - [c57]Junyeong Maeng, Kwanseok Oh, Heung-Il Suk:
Age-Aware Guidance via Masking-Based Attention in Face Aging. CIKM 2023: 4165-4169 - [c56]Jee Seok Yoon, Chenghao Zhang, Heung-Il Suk, Jia Guo, Xiaoxiao Li:
SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generation. IPMI 2023: 388-400 - [i24]Seungwoo Jeong, Wonsik Jung, Junghyo Sohn, Heung-Il Suk:
Deep Geometric Learning with Monotonicity Constraints for Alzheimer's Disease Progression. CoRR abs/2310.03353 (2023) - [i23]Wonsik Jung, Eunjin Jeon, Eunsong Kang, Heung-Il Suk:
EAG-RS: A Novel Explainability-guided ROI-Selection Framework for ASD Diagnosis via Inter-regional Relation Learning. CoRR abs/2310.03404 (2023) - [i22]Kwanseok Oh, Da-Woon Heo, Ahmad Wisnu Mulyadi, Wonsik Jung, Eunsong Kang, Kun Ho Lee, Heung-Il Suk:
A Quantitatively Interpretable Model for Alzheimer's Disease Prediction Using Deep Counterfactuals. CoRR abs/2310.03457 (2023) - [i21]Eunsong Kang, Da-Woon Heo, Jiwon Lee, Heung-Il Suk:
A Learnable Counter-condition Analysis Framework for Functional Connectivity-based Neurological Disorder Diagnosis. CoRR abs/2310.03964 (2023) - [i20]Jee Seok Yoon, Kwanseok Oh, Yooseung Shin, Maciej A. Mazurowski, Heung-Il Suk:
Domain Generalization for Medical Image Analysis: A Survey. CoRR abs/2310.08598 (2023) - [i19]Ahmad Wisnu Mulyadi, Heung-Il Suk:
KindMed: Knowledge-Induced Medicine Prescribing Network for Medication Recommendation. CoRR abs/2310.14552 (2023) - 2022
- [j37]Ahmad Wisnu Mulyadi, Eunji Jun, Heung-Il Suk:
Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series. IEEE Trans. Cybern. 52(9): 9684-9694 (2022) - [j36]Wonjun Ko, Eunjin Jeon, Heung-Il Suk:
A Novel RL-Assisted Deep Learning Framework for Task-Informative Signals Selection and Classification for Spontaneous BCIs. IEEE Trans. Ind. Informatics 18(3): 1873-1882 (2022) - [j35]Yurim Lee, Eunji Jun, Jaehun Choi, Heung-Il Suk:
Multi-View Integrative Attention-Based Deep Representation Learning for Irregular Clinical Time-Series Data. IEEE J. Biomed. Health Informatics 26(8): 4270-4280 (2022) - [j34]Wonjun Ko, Wonsik Jung, Eunjin Jeon, Heung-Il Suk:
A Deep Generative-Discriminative Learning for Multimodal Representation in Imaging Genetics. IEEE Trans. Medical Imaging 41(9): 2348-2359 (2022) - [j33]Jee Seok Yoon, Myung-Cheol Roh, Heung-Il Suk:
A Plug-in Method for Representation Factorization in Connectionist Models. IEEE Trans. Neural Networks Learn. Syst. 33(8): 3792-3803 (2022) - [c55]Seungwoo Jeong, Wonjun Ko, Ahmad Wisnu Mulyadi, Heung-Il Suk:
Continuous Riemannian Geometric Learning for Sleep Staging Classification. BCI 2022: 1-2 - [c54]Wonjun Ko, Heung-Il Suk:
EEG-Oriented Self-Supervised Learning and Cluster-Aware Adaptation. CIKM 2022: 4143-4147 - [c53]Jaeun Phyo, Wonjun Ko, Eunjin Jeon, Heung-Il Suk:
Enhancing Contextual Encoding With Stage-Confusion and Stage-Transition Estimation for EEG-Based Sleep Staging. ICASSP 2022: 1301-1305 - [c52]Seungwoo Jeong, Wonsik Jung, Junghyo Sohn, Heung-Il Suk:
Deep Geometrical Learning for Alzheimer's Disease Progression Modeling. ICDM 2022: 211-220 - [c51]Jieun Lee, Kwanseok Oh, Dinggang Shen, Heung-Il Suk:
A Novel Knowledge Keeper Network for 7T-Free but 7T-Guided Brain Tissue Segmentation. MICCAI (5) 2022: 330-339 - [c50]Eunsong Kang, Da-Woon Heo, Heung-Il Suk:
Prototype Learning of Inter-network Connectivity for ASD Diagnosis and Personalized Analysis. MICCAI (3) 2022: 334-343 - [i18]Jaeun Phyo, Wonjun Ko, Eunjin Jeon, Heung-Il Suk:
TransSleep: Transitioning-aware Attention-based Deep Neural Network for Sleep Staging. CoRR abs/2203.12590 (2022) - [i17]Ahmad Wisnu Mulyadi, Wonsik Jung, Kwanseok Oh, Jee Seok Yoon, Heung-Il Suk:
XADLiME: eXplainable Alzheimer's Disease Likelihood Map Estimation via Clinically-guided Prototype Learning. CoRR abs/2207.13223 (2022) - [i16]Jee Seok Yoon, Chenghao Zhang, Heung-Il Suk, Jia Guo, Xiaoxiao Li:
SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generation. CoRR abs/2212.08228 (2022) - 2021
- [j32]Wonjun Ko, Eunjin Jeon, Seungwoo Jeong, Heung-Il Suk:
Multi-Scale Neural Network for EEG Representation Learning in BCI. IEEE Comput. Intell. Mag. 16(2): 31-45 (2021) - [j31]Jiyeon Lee, Wonjun Ko, Eunsong Kang, Heung-Il Suk, Alzheimer's Disease Neuroimaging Initiative:
A unified framework for personalized regions selection and functional relation modeling for early MCI identification. NeuroImage 236: 118048 (2021) - [j30]Wonsik Jung, Eunji Jun, Heung-Il Suk, Alzheimer's Disease Neuroimaging Initiative:
Deep recurrent model for individualized prediction of Alzheimer's disease progression. NeuroImage 237: 118143 (2021) - [j29]Byoung-Kyong Min, Hyun Seok Kim, Wonjun Ko, Min-Hee Ahn, Heung-Il Suk, Dimitrios Pantazis, Robert T. Knight:
Electrophysiological Decoding of Spatial and Color Processing in Human Prefrontal Cortex. NeuroImage 237: 118165 (2021) - [j28]Eunji Jun, Ahmad Wisnu Mulyadi, Jaehun Choi, Heung-Il Suk:
Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction. IEEE Trans. Neural Networks Learn. Syst. 32(9): 4052-4062 (2021) - [c49]Wonjun Ko, Eunjin Jeon, Heung-Il Suk:
Spectro-Spatio-Temporal EEG Representation Learning for Imagined Speech Recognition. ACPR (2) 2021: 335-346 - [c48]Seungwoo Jeong, Eunjin Jeon, Wonjun Ko, Heung-Il Suk:
Fine-grained Temporal Attention Network for EEG-based Seizure Detection. BCI 2021: 1-4 - [c47]Wonjun Ko, Wonsik Jung, Eunjin Jeon, Ahmad Wisnu Mulyadi, Heung-Il Suk:
ENGINE: Enhancing Neuroimaging and Genetic Information by Neural Embedding. ICDM 2021: 1162-1167 - [c46]Wonsik Jung, Da-Woon Heo, Eunjin Jeon, Jaein Lee, Heung-Il Suk:
Inter-regional High-Level Relation Learning from Functional Connectivity via Self-supervision. MICCAI (2) 2021: 284-293 - [c45]Jaein Lee, Eunsong Kang, Eunjin Jeon, Heung-Il Suk:
Meta-modulation Network for Domain Generalization in Multi-site fMRI Classification. MICCAI (5) 2021: 500-509 - [i15]Yurim Lee, Eunji Jun, Heung-Il Suk:
Multi-view Integration Learning for Irregularly-sampled Clinical Time Series. CoRR abs/2101.09986 (2021) - [i14]Junghyo Sohn, Eunjin Jeon, Wonsik Jung, Eunsong Kang, Heung-Il Suk:
Fine-Grained Attention for Weakly Supervised Object Localization. CoRR abs/2104.04952 (2021) - [i13]Eunji Jun, Seungwoo Jeong, Da-Woon Heo, Heung-Il Suk:
Medical Transformer: Universal Brain Encoder for 3D MRI Analysis. CoRR abs/2104.13633 (2021) - [i12]Changhyun Park, Heung-Il Suk:
Deep Joint Learning of Pathological Region Localization and Alzheimer's Disease Diagnosis. CoRR abs/2108.04555 (2021) - [i11]Kwanseok Oh, Jee Seok Yoon, Heung-Il Suk:
Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model. CoRR abs/2108.09451 (2021) - [i10]Seungwoo Jeong, Wonjun Ko, Ahmad Wisnu Mulyadi, Heung-Il Suk:
Efficient Continuous Manifold Learning for Time Series Modeling. CoRR abs/2112.03379 (2021) - 2020
- [j27]Yinghuan Shi, Heung-Il Suk, Yang Gao, Seong-Whan Lee, Dinggang Shen:
Leveraging Coupled Interaction for Multimodal Alzheimer's Disease Diagnosis. IEEE Trans. Neural Networks Learn. Syst. 31(1): 186-200 (2020) - [c44]Wonjun Ko, Kwanseok Oh, Eunjin Jeon, Heung-Il Suk:
VIGNet: A Deep Convolutional Neural Network for EEG-based Driver Vigilance Estimation. BCI 2020: 1-3 - [c43]Eunjin Jeon, Eunsong Kang, Jiyeon Lee, Jaein Lee, Tae-Eui Kam, Heung-Il Suk:
Enriched Representation Learning in Resting-State fMRI for Early MCI Diagnosis. MICCAI (7) 2020: 397-406 - [i9]Eunji Jun, Ahmad Wisnu Mulyadi, Jaehun Choi, Heung-Il Suk:
Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction. CoRR abs/2003.00655 (2020) - [i8]Ahmad Wisnu Mulyadi, Eunji Jun, Heung-Il Suk:
Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series. CoRR abs/2003.00662 (2020) - [i7]Wonjun Ko, Eunjin Jeon, Seungwoo Jeong, Heung-Il Suk:
Multi-Scale Neural network for EEG Representation Learning in BCI. CoRR abs/2003.02657 (2020) - [i6]Wonsik Jung, Eunji Jun, Heung-Il Suk:
Deep Recurrent Disease Progression Model for Conversion-Time Prediction of Alzheimer's Disease. CoRR abs/2005.02643 (2020) - [i5]Wonjun Ko, Eunjin Jeon, Heung-Il Suk:
A Novel RL-assisted Deep Learning Framework for Task-informative Signals Selection and Classification for Spontaneous BCIs. CoRR abs/2007.00162 (2020) - [i4]Kwanseok Oh, Jee Seok Yoon, Heung-Il Suk:
Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decision. CoRR abs/2011.10381 (2020)
2010 – 2019
- 2019
- [j26]Li Wang, Yinghuan Shi, Heung-Il Suk, J. Alison Noble, Ghassan Hamarneh:
Special issue on machine learning in medical imaging. Comput. Medical Imaging Graph. 74: 10-11 (2019) - [j25]Eunji Jun, Eunsong Kang, Jaehun Choi, Heung-Il Suk:
Modeling regional dynamics in low-frequency fluctuation and its application to Autism spectrum disorder diagnosis. NeuroImage 184: 669-686 (2019) - [j24]Eunho Lee, Jun-Sik Choi, Minjeong Kim, Heung-Il Suk, Alzheimer's Disease Neuroimaging Initiative:
Toward an interpretable Alzheimer's disease diagnostic model with regional abnormality representation via deep learning. NeuroImage 202 (2019) - [j23]Bum-Chae Kim, Jee Seok Yoon, Jun-Sik Choi, Heung-Il Suk:
Multi-scale gradual integration CNN for false positive reduction in pulmonary nodule detection. Neural Networks 115: 1-10 (2019) - [j22]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Group sparse reduced rank regression for neuroimaging genetic study. World Wide Web 22(2): 673-688 (2019) - [j21]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Low-rank dimensionality reduction for multi-modality neurodegenerative disease identification. World Wide Web 22(2): 907-925 (2019) - [c42]Eunjin Jeon, Wonjun Ko, Heung-Il Suk:
Domain Adaptation with Source Selection for Motor-Imagery based BCI. BCI 2019: 1-4 - [c41]Wonjun Ko, Eunjin Jeon, Jiyeon Lee, Heung-Il Suk:
Semi-Supervised Deep Adversarial Learning for Brain-Computer Interface. BCI 2019: 1-4 - [c40]Eunji Jun, Ahmad Wisnu Mulyadi, Heung-Il Suk:
Stochastic Imputation and Uncertainty-Aware Attention to EHR for Mortality Prediction. IJCNN 2019: 1-7 - [c39]Wonsik Jung, Ahmad Wisnu Mulyadi, Heung-Il Suk:
Unified Modeling of Imputation, Forecasting, and Prediction for AD Progression. MICCAI (4) 2019: 168-176 - [e4]Heung-Il Suk, Mingxia Liu, Pingkun Yan, Chunfeng Lian:
Machine Learning in Medical Imaging - 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings. Lecture Notes in Computer Science 11861, Springer 2019, ISBN 978-3-030-32691-3 [contents] - [i3]Jee Seok Yoon, Wonjun Ko, Heung-Il Suk:
Plug-in Factorization for Latent Representation Disentanglement. CoRR abs/1905.11088 (2019) - [i2]Eunjin Jeon, Wonjun Ko, Jee Seok Yoon, Heung-Il Suk:
Toward Subject Invariant and Class Disentangled Representation in BCI via Cross-Domain Mutual Information Estimator. CoRR abs/1910.07747 (2019) - 2018
- [c38]Wonjun Ko, Jee Seok Yoon, Eunsong Kang, Eunji Jun, Jun-Sik Choi, Heung-Il Suk:
Deep recurrent spatio-temporal neural network for motor imagery based BCI. BCI 2018: 1-3 - [c37]Jun-Sik Choi, Eunho Lee, Heung-Il Suk:
Regional Abnormality Representation Learning in Structural MRI for AD/MCI Diagnosis. MLMI@MICCAI 2018: 64-72 - [c36]Eunsong Kang, Heung-Il Suk:
Probabilistic Source Separation on Resting-State fMRI and Its Use for Early MCI Identification. MICCAI (3) 2018: 275-283 - [e3]Yinghuan Shi, Heung-Il Suk, Mingxia Liu:
Machine Learning in Medical Imaging - 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. Lecture Notes in Computer Science 11046, Springer 2018, ISBN 978-3-030-00918-2 [contents] - [i1]Bum-Chae Kim, Jun-Sik Choi, Heung-Il Suk:
Multi-Scale Gradual Integration CNN for False Positive Reduction in Pulmonary Nodule Detection. CoRR abs/1807.10581 (2018) - 2017
- [j20]Heung-Il Suk, Seong-Whan Lee, Dinggang Shen:
Deep ensemble learning of sparse regression models for brain disease diagnosis. Medical Image Anal. 37: 101-113 (2017) - [j19]Xiaofeng Zhu, Heung-Il Suk, Li Wang, Seong-Whan Lee, Dinggang Shen:
A novel relational regularization feature selection method for joint regression and classification in AD diagnosis. Medical Image Anal. 38: 205-214 (2017) - [j18]Xiaofeng Zhu, Heung-Il Suk, Heng Huang, Dinggang Shen:
Low-Rank Graph-Regularized Structured Sparse Regression for Identifying Genetic Biomarkers. IEEE Trans. Big Data 3(4): 405-414 (2017) - [j17]Byoung-Kyong Min, Heung-Il Suk, Min-Hee Ahn, Min-Ho Lee, Seong-Whan Lee:
Individual Identification Using Cognitive Electroencephalographic Neurodynamics. IEEE Trans. Inf. Forensics Secur. 12(9): 2159-2167 (2017) - [c35]Eunji Jun, Heung-Il Suk:
Region-Wise Stochastic Pattern Modeling for Autism Spectrum Disorder Identification and Temporal Dynamics Analysis. CNI@MICCAI 2017: 143-151 - [p1]Heung-Il Suk:
An Introduction to Neural Networks and Deep Learning. Deep Learning for Medical Image Analysis 2017: 3-24 - [e2]Qian Wang, Yinghuan Shi, Heung-Il Suk, Kenji Suzuki:
Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings. Lecture Notes in Computer Science 10541, Springer 2017, ISBN 978-3-319-67388-2 [contents] - 2016
- [j16]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) - [j15]Xiaofeng Zhu, Heung-Il Suk, Seong-Whan Lee, Dinggang Shen:
Subspace Regularized Sparse Multitask Learning for Multiclass Neurodegenerative Disease Identification. IEEE Trans. Biomed. Eng. 63(3): 607-618 (2016) - [j14]Zhou Li, Heung-Il Suk, Dinggang Shen, Lexin Li:
Sparse Multi-Response Tensor Regression for Alzheimer's Disease Study With Multivariate Clinical Assessments. IEEE Trans. Medical Imaging 35(8): 1927-1936 (2016) - [c34]Eunsong Kang, Bum-Chae Kim, Heung-Il Suk:
An empirical suggestion for collaborative learning in motor imagery-based BCIs. BCI 2016: 1-3 - [c33]Bum-Chae Kim, Yu Sub Sung, Heung-Il Suk:
Deep feature learning for pulmonary nodule classification in a lung CT. BCI 2016: 1-3 - [c32]Xiaofeng Zhu, Heung-Il Suk, Kim-Han Thung, Yingying Zhu, Guorong Wu, Dinggang Shen:
Joint Discriminative and Representative Feature Selection for Alzheimer's Disease Diagnosis. MLMI@MICCAI 2016: 77-85 - [c31]Heung-Il Suk, Dinggang Shen:
Deep Ensemble Sparse Regression Network for Alzheimer's Disease Diagnosis. MLMI@MICCAI 2016: 113-121 - [c30]Xiaofeng Zhu, Heung-Il Suk, Heng Huang, Dinggang Shen:
Structured Sparse Low-Rank Regression Model for Brain-Wide and Genome-Wide Associations. MICCAI (1) 2016: 344-352 - [e1]Li Wang, Ehsan Adeli, Qian Wang, Yinghuan Shi, Heung-Il Suk:
Machine Learning in Medical Imaging - 7th International Workshop, MLMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings. Lecture Notes in Computer Science 10019, 2016, ISBN 978-3-319-47156-3 [contents] - 2015
- [j13]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) - [j12]Dong-Gyu Lee, Heung-Il Suk, Sung-Kee Park, Seong-Whan Lee:
Motion Influence Map for Unusual Human Activity Detection and Localization in Crowded Scenes. IEEE Trans. Circuits Syst. Video Technol. 25(10): 1612-1623 (2015) - [c29]Jeong-Woo Kim, Heung-Il Suk, Jong-Pil Kim, Seong-Whan Lee:
Combined regression and classification approach for prediction of driver's braking intention. BCI 2015: 1-3 - [c28]Xiaofeng Zhu, Heung-Il Suk, Yonghua Zhu, Kim-Han Thung, Guorong Wu, Dinggang Shen:
Multi-view Classification for Identification of Alzheimer's Disease. MLMI 2015: 255-262 - [c27]Heung-Il Suk, Seong-Whan Lee, Dinggang Shen:
A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI. MICCAI (1) 2015: 573-580 - 2014
- [j11]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
A novel matrix-similarity based loss function for joint regression and classification in AD diagnosis. NeuroImage 100: 91-105 (2014) - [j10]Heung-Il Suk, Seong-Whan Lee, Dinggang Shen:
Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis. NeuroImage 101: 569-582 (2014) - [c26]Dong-Gyu Lee, Heung-Il Suk, Seong-Whan Lee:
Modeling crowd motions for abnormal activity detection. AVSS 2014: 325-330 - [c25]Yinghuan Shi, Heung-Il Suk, Yang Gao, Dinggang Shen:
Joint Coupled-Feature Representation and Coupled Boosting for AD Diagnosis. CVPR 2014: 2721-2728 - [c24]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Matrix-Similarity Based Loss Function and Feature Selection for Alzheimer's Disease Diagnosis. CVPR 2014: 3089-3096 - [c23]Areum Lee, Heung-Il Suk, Seong-Whan Lee:
View-Invariant 3D Action Recognition Using Spatiotemporal Self-Similarities from Depth Camera. ICPR 2014: 501-505 - [c22]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Sparse Discriminative Feature Selection for Multi-class Alzheimer's Disease Classification. MLMI 2014: 157-164 - [c21]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Multi-modality Canonical Feature Selection for Alzheimer's Disease Diagnosis. MICCAI (2) 2014: 162-169 - [c20]Xuchu Wang, Li Wang, Heung-Il Suk, Dinggang Shen:
Online Discriminative Multi-atlas Learning for Isointense Infant Brain Segmentation. MLMI 2014: 297-305 - [c19]Rongjian Li, Wenlu Zhang, Heung-Il Suk, Li Wang, Jiang Li, Dinggang Shen, Shuiwang Ji:
Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis. MICCAI (3) 2014: 305-312 - [c18]Heung-Il Suk, Dinggang Shen:
Clustering-Induced Multi-task Learning for AD/MCI Classification. MICCAI (3) 2014: 393-400 - [c17]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
A Novel Multi-relation Regularization Method for Regression and Classification in AD Diagnosis. MICCAI (3) 2014: 401-408 - 2013
- [j9]Tae-Eui Kam, Heung-Il Suk, Seong-Whan Lee:
Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification. Neurocomputing 108: 58-68 (2013) - [j8]Heung-Il Suk, Seong-Whan Lee:
A Novel Bayesian Framework for Discriminative Feature Extraction in Brain-Computer Interfaces. IEEE Trans. Pattern Anal. Mach. Intell. 35(2): 286-299 (2013) - [j7]Seul-Ki Yeom, Heung-Il Suk, Seong-Whan Lee:
Person authentication from neural activity of face-specific visual self-representation. Pattern Recognit. 46(4): 1159-1169 (2013) - [c16]Dong-Gyu Lee, Heung-Il Suk, Seong-Whan Lee:
Crowd Behavior Representation Using Motion Influence Matrix for Anomaly Detection. ACPR 2013: 110-114 - [c15]Heung-Il Suk, Seong-Whan Lee:
A Bayesian approach for spatio-spectral filter optimization in BCI. BCI 2013: 22-23 - [c14]Tae-Eui Kam, Heung-Il Suk, Seong-Whan Lee:
Non-homogeneous spatial filter optimization for EEG-based brain-computer interfaces. BCI 2013: 26-28 - [c13]Seul-Ki Yeom, Heung-Il Suk, Seong-Whan Lee:
Eeg-based person authentication using face stimuli. BCI 2013: 58-61 - [c12]Biao Jie, Daoqiang Zhang, Heung-Il Suk, Chong-Yaw Wee, Dinggang Shen:
Integrating Multiple Network Properties for MCI Identification. MLMI 2013: 9-16 - [c11]Heung-Il Suk, Chong-Yaw Wee, Dinggang Shen:
Discriminative Group Sparse Representation for Mild Cognitive Impairment Classification. MLMI 2013: 131-138 - [c10]Manhua Liu, Heung-Il Suk, Dinggang Shen:
Multi-task Sparse Classifier for Diagnosis of MCI Conversion to AD with Longitudinal MR Images. MLMI 2013: 243-250 - [c9]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 - [c8]Heung-Il Suk, Dinggang Shen:
Deep Learning-Based Feature Representation for AD/MCI Classification. MICCAI (2) 2013: 583-590 - 2012
- [j6]Heung-Il Suk, Yuzhuo Wang, Seong-Whan Lee:
Incremental Sparse Pseudo-input Gaussian Process Regression. Int. J. Pattern Recognit. Artif. Intell. 26(8) (2012) - [j5]Dongcheol Hur, Heung-Il Suk, Christian Wallraven, Seong-Whan Lee:
Biased Manifold Learning for View Invariant Body Pose Estimation. Int. J. Wavelets Multiresolution Inf. Process. 10(6) (2012) - [j4]Hee-Deok Yang, Heung-Il Suk, Seong-Whan Lee:
Accelerating generalized Iterative Scaling Based on Staggered Aitken Method for on-Line Conditional Random Fields. Int. J. Wavelets Multiresolution Inf. Process. 10(6) (2012) - [c7]Heung-Il Suk, Yuzhuo Wang, Seong-Whan Lee:
Online learning of sparse pseudo-input Gaussian Process. SMC 2012: 1357-1360 - 2011
- [j3]Heung-Il Suk, Seong-Whan Lee:
Subject and class specific frequency bands selection for multiclass motor imagery classification. Int. J. Imaging Syst. Technol. 21(2): 123-130 (2011) - [j2]Heung-Il Suk, Anil K. Jain, Seong-Whan Lee:
A Network of Dynamic Probabilistic Models for Human Interaction Analysis. IEEE Trans. Circuits Syst. Video Technol. 21(7): 932-945 (2011) - [c6]Heung-Il Suk, Seong-Whan Lee:
Data-Driven Frequency Bands Selection in EEG-Based Brain-Computer Interface. PRNI 2011: 25-28 - [c5]Heung-Il Suk, Seong-Whan Lee:
A probabilistic approach to spatio-spectral filters optimization in Brain-Computer Interface. SMC 2011: 19-24 - 2010
- [j1]Heung-Il Suk, Bong-Kee Sin, Seong-Whan Lee:
Hand gesture recognition based on dynamic Bayesian network framework. Pattern Recognit. 43(9): 3059-3072 (2010)
2000 – 2009
- 2009
- [c4]Heung-Il Suk, Bong-Kee Sin, Seong-Whan Lee:
Analyzing human interactions with a network of dynamic probabilistic models. WACV 2009: 1-6 - 2008
- [c3]Heung-Il Suk, Bong-Kee Sin, Seong-Whan Lee:
Recognizing hand gestures using dynamic Bayesian network. FG 2008: 1-6 - [c2]Heung-Il Suk, Bong-Kee Sin, Seong-Whan Lee:
Robust modeling and recognition of hand gestures with dynamic Bayesian network. ICPR 2008: 1-4 - 2006
- [c1]Heung-Il Suk, Bong-Kee Sin:
HMM-Based Gait Recognition with Human Profiles. SSPR/SPR 2006: 596-603
Coauthor Index
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