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Seong-Whan Lee

Seong-Whan Lee

Award Badge
Computer Science
Korea
2026

D-Index & Metrics

Computer Science

D-Index
82
Citations
25454
World Ranking
968
National Ranking
3

Research.com Recognitions

  • 2026 - Research.com Computer Science in Korea Leader Award
  • 2025 - Research.com Computer Science in Korea Leader Award
  • 2024 - Research.com Computer Science in Korea Leader Award
  • 2023 - Fellow of the National Academy of Engineering of Korea (NAEK)
  • 2023 - Research.com Computer Science in Korea Leader Award
  • 2022 - Research.com Computer Science in Korea Leader Award
  • 2010 - IEEE Fellow For contributions to pattern recognition for biometrics and document image analysis
  • 2009 - Fellow of the Korean Academy of Science and Technology (KAST)
  • 1998 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to document understanding and for service to IAPR

Overview

Seong-Whan Lee is affiliated with Korea University in South Korea and has an extensive publication record primarily in the fields of Computer Science and Neuroscience. Their work spans several subfields including Cognitive Neuroscience, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, and Electrical and Electronic Engineering.

The research topics covered by Seong-Whan Lee focus mainly on EEG and Brain-Computer Interfaces, Advanced Memory and Neural Computing, Neural Dynamics and Brain Function, Gaze Tracking and Assistive Technology, Speech Recognition and Synthesis, Human Pose and Action Recognition, and Functional Brain Connectivity Studies.

Some of the recent papers authored include:

  • Brain-Controlled Robotic Arm System Based on Multi-Directional CNN-BiLSTM Network Using EEG Signals, 2020, IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • Adaptive Transfer Learning for EEG Motor Imagery Classification with Deep Convolutional Neural Network, 2020, Neural Networks
  • Spatio-Spectral Feature Representation for Motor Imagery Classification Using Convolutional Neural Networks, 2021, IEEE Transactions on Neural Networks and Learning Systems
  • Neural Decoding of Imagined Speech and Visual Imagery as Intuitive Paradigms for BCI Communication, 2020, IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface, 2021, arXiv (Cornell University)

Frequent co-authors in their collaborative work include Ji-Hoon Jeong, Minji Lee, Dinggang Shen, Woo-Jeoung Nam, and Gi-Hwan Shin.

The scientist often publishes in venues such as arXiv (Cornell University), UNC Libraries, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Neural Networks, and Pattern Recognition.

Seong-Whan Lee has received several awards recognizing their contributions to the scientific community. These include being named an IEEE Fellow in 2010 for contributions to pattern recognition related to biometrics and document image analysis, a Fellow of the Korean Academy of Science and Technology (KAST) in 2009, and a Fellow of the International Association for Pattern Recognition (IAPR) in 1998 for contributions to document understanding and professional service.

Best Publications

  • Thinning methodologies—a comprehensive survey

    Louisa Lam;Seong-Whan Lee;Ching Y. Suen

  • The Role of Context for Object Detection and Semantic Segmentation in the Wild

    Roozbeh Mottaghi;Xianjie Chen;Xiaobai Liu;Nam-Gyu Cho

  • Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis.

    Heung-Il Suk;Seong-Whan Lee;Dinggang Shen

  • Latent feature representation with stacked auto-encoder for AD/MCI diagnosis

    Heung Il Suk;Seong Whan Lee;Dinggang Shen;Dinggang Shen

  • Applications of Support Vector Machines for Pattern Recognition: A Survey

    Hyeran Byun;Seong-Whan Lee

  • EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy.

    Minho Lee;O-Yeon Kwon;Yong-Jeong Kim;Hong-Kyung Kim

  • Advances in Biometrics

    Seong-Whan Lee;Stan Z. Li

  • State-space model with deep learning for functional dynamics estimation in resting-state fMRI

    Heung Il Suk;Chong Yaw Wee;Seong Whan Lee;Dinggang Shen

  • Subject-Independent Brain–Computer Interfaces Based on Deep Convolutional Neural Networks

    O-Yeon Kwon;Min-Ho Lee;Cuntai Guan;Seong-Whan Lee

  • Deep ensemble learning of sparse regression models for brain disease diagnosis

    Heung Il Suk;Seong Whan Lee;Dinggang Shen;Dinggang Shen

  • Biologically Motivated Computer Vision: Second International Workshop

    HH Bülthoff;Lee S-W, Poggio, Ta;C Wallraven

  • Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network

    Seong-Whan Lee

  • A convolutional neural network for steady state visual evoked potential classification under ambulatory environment.

    No Sang Kwak;Klaus Robert Müller;Klaus Robert Müller;Seong Whan Lee

  • Sign Language Spotting with a Threshold Model Based on Conditional Random Fields

    H.-D. Yang;S. Sclaroff;S.-W. Lee

  • A SURVEY ON PATTERN RECOGNITION APPLICATIONS OF SUPPORT VECTOR MACHINES

    Hyeran Byun;Seong Whan Lee

  • AdaBoost for Text Detection in Natural Scene

    Jung-Jin Lee;Pyoung-Hean Lee;Seong-Whan Lee;Alan Yuille

  • Brain-Controlled Robotic Arm System Based on Multi-Directional CNN-BiLSTM Network Using EEG Signals

    Ji-Hoon Jeong;Kyung-Hwan Shim;Dong-Joo Kim;Seong-Whan Lee

  • A Novel Bayesian Framework for Discriminative Feature Extraction in Brain-Computer Interfaces

    Heung-Il Suk;Seong-Whan Lee

  • Adaptive transfer learning for EEG motor imagery classification with deep Convolutional Neural Network.

    Kaishuo Zhang;Neethu Robinson;Seong Whan Lee;Cuntai Guan

  • A novel relational regularization feature selection method for joint regression and classification in AD diagnosis

    Xiaofeng Zhu;Heung-Il Suk;Li Wang;Seong-Whan Lee

  • A new methodology for gray-scale character segmentation and recognition

    Seong-Whan Lee;Dong-June Lee;Dong-June Lee;Hee-Seon Park;Hee-Seon Park

  • Hand gesture recognition based on dynamic Bayesian network framework

    Heung-Il Suk;Bong-Kee Sin;Seong-Whan Lee

  • Fast scene change detection using direct feature extraction from MPEG compressed videos

    Seong-Whan Lee;Young-Min Kim;Sung Woo Choi

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Heung-Il Suk
Heung-Il Suk Korea University
Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Anil K. Jain
Anil K. Jain Michigan State University
Yuan Yan Tang
Yuan Yan Tang University of Macau
Heinrich H. Bülthoff
Heinrich H. Bülthoff Max Planck Institute for Biological Cybernetics
Christian Wallraven
Christian Wallraven Korea University
Han Zhang
Han Zhang ShanghaiTech University
Cuntai Guan
Cuntai Guan Nanyang Technological University
Giulio Tononi
Giulio Tononi University of Wisconsin–Madison

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