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Employment (1)

Gwangju Institute of Science and Technology: Gwangju, KR

(School of Integrated Technology)
Employment
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Deok-Won Lee

Works (9)

Development of a Multiple RGB-D Sensor System for ADHD Screening and Improvement of Classification Performance Using Feature Selection Method

Applied Sciences
2023-02-22 | Journal article
Contributors: Deok-Won Lee; Sang-hyub Lee; Dong Hyun Ahn; Ga Hyun Lee; Kooksung Jun; Mun Sang Kim
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A Deep Learning-Based Semantic Segmentation Model Using MCNN and Attention Layer for Human Activity Recognition

Sensors
2023-02-17 | Journal article
Contributors: Sang-hyub Lee; Deok-Won Lee; Mun Sang Kim
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Deep Learning-Based ADHD and ADHD-RISK Classification Technology through the Recognition of Children’s Abnormal Behaviors during the Robot-Led ADHD Screening Game

Sensors
2022-12-27 | Journal article
Contributors: Wonjun Lee; Sanghyub Lee; Deokwon Lee; Kooksung Jun; Dong Hyun Ahn; Mun Sang Kim
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Deep-Learning-Based ADHD Classification Using Children’s Skeleton Data Acquired through the ADHD Screening Game

Sensors
2022-12-26 | Journal article
Contributors: Wonjun Lee; Deokwon Lee; Sanghyub Lee; Kooksung Jun; Mun Sang Kim
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Markerless 3D Skeleton Tracking Algorithm by Merging Multiple Inaccurate Skeleton Data from Multiple RGB-D Sensors

Sensors
2022-04-20 | Journal article
Contributors: Sang-hyub Lee; Deok-Won Lee; Kooksung Jun; Wonjun Lee; Mun Sang Kim
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Deep Learning-Based Multimodal Abnormal Gait Classification Using a 3D Skeleton and Plantar Foot Pressure

IEEE Access
2021 | Journal article
Contributors: Kooksung Jun; Sanghyub Lee; Deok-Won Lee; Mun Sang Kim
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Deep Neural Network–Based Double-Check Method for Fall Detection Using IMU-L Sensor and RGB Camera Data

IEEE Access
2021 | Journal article
Contributors: Deok-Won Lee; Kooksung Jun; Khawar Naheem; Mun Sang Kim
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Feature Extraction Using an RNN Autoencoder for Skeleton-Based Abnormal Gait Recognition

IEEE Access
2020 | Journal article
Contributors: Kooksung Jun; Deok-Won Lee; Kyoobin Lee; Sanghyub Lee; Mun Sang Kim
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Pathological Gait Classification Using Kinect v2 and Gated Recurrent Neural Networks

IEEE Access
2020 | Journal article
Contributors: Kooksung Jun; Yongwoo Lee; Sanghyub Lee; Deok-Won Lee; Mun Sang Kim
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