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Seong-Whan Lee
Seong-Whan Lee
Professor of Artificial Intelligence and Brain Engineering, Korea University
Verified email at korea.ac.kr - Homepage
Title
Cited by
Cited by
Year
Thinning methodologies-a comprehensive survey
L Lam, SW Lee, CY Suen
IEEE Transactions on Pattern Analysis & Machine Intelligence 14 (09), 869-885, 1992
26191992
The role of context for object detection and semantic segmentation in the wild
R Mottaghi, X Chen, X Liu, NG Cho, SW Lee, S Fidler, R Urtasun, A Yuille
Proceedings of the IEEE conference on computer vision and pattern …, 2014
15292014
Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis
HI Suk, SW Lee, D Shen, Alzheimer's Disease Neuroimaging Initiative
NeuroImage 101, 569-582, 2014
9462014
Latent feature representation with stacked auto-encoder for AD/MCI diagnosis
HI Suk, SW Lee, D Shen, Alzheimer’s Disease Neuroimaging Initiative
Brain Structure and Function 220, 841-859, 2015
5652015
Applications of support vector machines for pattern recognition: A survey
H Byun, SW Lee
International workshop on support vector machines, 213-236, 2002
5462002
Hybrid high-order functional connectivity networks using resting-state functional MRI for mild cognitive impairment diagnosis
Y Zhang, H Zhang, X Chen, SW Lee, D Shen
Scientific reports 7 (1), 6530, 2017
3702017
EEG dataset and OpenBMI toolbox for three BCI paradigms: An investigation into BCI illiteracy
MH Lee, OY Kwon, YJ Kim, HK Kim, YE Lee, J Williamson, S Fazli, ...
GigaScience 8 (5), giz002, 2019
3442019
State-space model with deep learning for functional dynamics estimation in resting-state fMRI
HI Suk, CY Wee, SW Lee, D Shen
NeuroImage 129, 292-307, 2016
3212016
Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network
SW Lee
IEEE Transactions on Pattern Analysis and Machine Intelligence 18 (6), 648-652, 1996
2981996
A survey on pattern recognition applications of support vector machines
H Byun, SW Lee
International Journal of Pattern Recognition and Artificial Intelligence 17 …, 2003
2932003
Deep ensemble learning of sparse regression models for brain disease diagnosis
HI Suk, SW Lee, D Shen, Alzheimer’s Disease Neuroimaging Initiative
Medical image analysis 37, 101-113, 2017
2912017
Adaboost for text detection in natural scene
JJ Lee, PH Lee, SW Lee, A Yuille, C Koch
2011 International conference on document analysis and recognition, 429-434, 2011
2882011
A convolutional neural network for steady state visual evoked potential classification under ambulatory environment
NS Kwak, KR Müller, SW Lee
PloS one 12 (2), e0172578, 2017
2852017
Sign language spotting with a threshold model based on conditional random fields
HD Yang, S Sclaroff, SW Lee
IEEE transactions on pattern analysis and machine intelligence 31 (7), 1264-1277, 2008
2852008
Subject-independent brain–computer interfaces based on deep convolutional neural networks
OY Kwon, MH Lee, C Guan, SW Lee
IEEE transactions on neural networks and learning systems 31 (10), 3839-3852, 2019
2662019
A novel Bayesian framework for discriminative feature extraction in brain-computer interfaces
HI Suk, SW Lee
IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (2), 286-299, 2012
2492012
Hand gesture recognition based on dynamic Bayesian network framework
HI Suk, BK Sin, SW Lee
Pattern recognition 43 (9), 3059-3072, 2010
2492010
A new methodology for gray-scale character segmentation and recognition
SW Lee, DJ Lee, HS Park
IEEE transactions on pattern analysis and machine intelligence 18 (10), 1045 …, 1996
2451996
A lower limb exoskeleton control system based on steady state visual evoked potentials
NS Kwak, KR Müller, SW Lee
Journal of neural engineering 12 (5), 056009, 2015
2432015
Fast scene change detection using direct feature extraction from MPEG compressed videos
SW Lee, YM Kim, SW Choi
IEEE Transactions on multimedia 2 (4), 240-254, 2000
2392000
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