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ORCIDKeun-Chang Kwak 0001
Person information
- affiliation: Chosun University, Department of Electronics Engineering, Gwangju, Korea
Other persons with the same name
- Keun-Chang Kwak — disambiguation page
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2020 – today
- 2022
[j22]Jae-Neung Lee, Keun-Chang Kwak
:
ECG-Based Biometrics Using a Deep Network Based on Independent Component Analysis. IEEE Access 10: 12913-12926 (2022)- [j21]A-Hyeon Jo, Keun-Chang Kwak:
Diagnosis of Depression Based on Four-Stream Model of Bi-LSTM and CNN From Audio and Text Information. IEEE Access 10: 134113-134135 (2022) - [j20]Yeong-Hyeon Byeon, Keun-Chang Kwak:
Individual Identification by Late Information Fusion of EmgCNN and EmgLSTM from Electromyogram Signals. Sensors 22(18): 6770 (2022) - [c13]Yeong-Hyeon Byeon, Keun-Chang Kwak:
Performance Comparison for Deep Learning-Based Personal Identification from the database of ECG and EMG singals. IEEE Big Data 2022: 6733-6735 - 2021
- [j19]Yeong-Hyeon Byeon, Dohyung Kim, Jaeyeon Lee, Keun-Chang Kwak:
Ensemble Three-Stream RGB-S Deep Neural Network for Human Behavior Recognition Under Intelligent Home Service Robot Environments. IEEE Access 9: 73240-73250 (2021) - [j18]Yeong-Hyeon Byeon, Dohyung Kim, Jaeyeon Lee, Keun-Chang Kwak:
Body and Hand-Object ROI-Based Behavior Recognition Using Deep Learning. Sensors 21(5): 1838 (2021) - 2020
- [j17]Myung-Won Lee, Keun-Chang Kwak:
Optimization by Context Refinement for Development of Incremental Granular Models. Symmetry 12(11): 1916 (2020)
2010 – 2019
- 2019
- [j16]Jae-Neung Lee, Keun-Chang Kwak:
Personal Identification Using a Robust Eigen ECG Network Based on Time-Frequency Representations of ECG Signals. IEEE Access 7: 48392-48404 (2019) - [j15]Yeong-Hyeon Byeon, Sung Bum Pan, Keun-Chang Kwak:
Intelligent Deep Models Based on Scalograms of Electrocardiogram Signals for Biometrics. Sensors 19(4): 935 (2019) - [j14]Chan-Uk Yeom, Keun-Chang Kwak:
Incremental Granular Model Improvement Using Particle Swarm Optimization. Symmetry 11(3): 390 (2019) - [j13]Chan-Uk Yeom, Keun-Chang Kwak:
Performance Evaluation of Automobile Fuel Consumption Using a Fuzzy-Based Granular Model with Coverage and Specificity. Symmetry 11(12): 1480 (2019) - [c12]Jae-Neung Lee, Sung Bum Pan, Keun-Chang Kwak:
Individual identification Based on Cascaded PCANet from ECG Signal. ICEIC 2019: 1-4 - 2018
- [j12]Jae-Neung Lee, Yeong-Hyeon Byeon, Sung Bum Pan, Keun-Chang Kwak:
An EigenECG Network Approach Based on PCANet for Personal Identification from ECG Signal. Sensors 18(11): 4024 (2018) - [j11]Yeong-Hyeon Byeon, Jae-Neung Lee, Sung Bum Pan, Keun-Chang Kwak:
Multilinear EigenECGs and FisherECGs for Individual Identification from Information Obtained by an Electrocardiogram Sensor. Symmetry 10(10): 487 (2018) - [j10]Chan-Uk Yeom, Keun-Chang Kwak:
Performance Comparison of ANFIS Models by Input Space Partitioning Methods. Symmetry 10(12): 700 (2018) - [c11]Yeong-Hyeon Byeon, Sung Bum Pan, Keun-Chang Kwak:
Individual Identification using Third-Order Tensor-Based Multilinear FisherECG. EECS 2018: 454-457 - 2017
- [j9]Dohyung Kim, Donghyeon Kim, Keun-Chang Kwak:
Classification of K-Pop Dance Movements Based on Skeleton Information Obtained by a Kinect Sensor. Sensors 17(6): 1261 (2017) - [j8]Chan-Uk Yeom, Keun-Chang Kwak:
The Development of Improved Incremental Models Using Local Granular Networks with Error Compensation. Symmetry 9(11): 266 (2017) - [j7]Yeong-Hyeon Byeon, Keun-Chang Kwak:
A Design for Genetically Oriented Rules-Based Incremental Granular Models and Its Application. Symmetry 9(12): 324 (2017) - [c10]Jung-Soo Han, Geum-Bae Cho, Keun-Chang Kwak:
A Design of Convolutional Neural Network Using ReLU-Based ELM Classifier and Its Application. ICMLC 2017: 179-183 - [c9]Yeong-Hyeon Byeon, Keun-Chang Kwak:
A Performance Comparison of Pedestrian Detection Using Faster RCNN and ACF. IIAI-AAI 2017: 858-863 - 2016
- [j6]Myungwon Lee, Keun-Chang Kwak:
An Incremental Radial Basis Function Network Based on Information Granules and Its Application. Comput. Intell. Neurosci. 2016: 3207627:1-3207627:6 (2016) - [j5]Jae-Neung Lee, Myungwon Lee, Yeong-Hyeon Byeon, Wonsik Lee, Keun-Chang Kwak:
Classification of Horse Gaits Using FCM-Based Neuro-Fuzzy Classifier from the Transformed Data Information of Inertial Sensor. Sensors 16(5): 664 (2016) - [j4]Meina Li, Keun-Chang Kwak, Youn Tae Kim:
Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network. Sensors 16(10): 1566 (2016) - [c8]Myungwon Lee, Keun-Chang Kwak, Witold Pedrycz:
An expansion of local Granular Models in the design of incremental model. FUZZ-IEEE 2016: 1664-1670 - [c7]Keun-Chang Kwak, Myungwon Lee:
Speech Enhancement Using ES Information and Phase-Error Based Filters. ICITCS 2016: 1-3 - 2015
- [c6]Yeong-Hyeon Byeon, Keun-Chang Kwak:
Knowledge Discovery and Modeling based on Conditional Fuzzy Clustering with Interval Type-2 Fuzzy. KDIR 2015: 440-444 - 2012
- [j3]Meina Li, Keun-Chang Kwak, Youn Tae Kim:
Intelligent Predictor of Energy Expenditure with the Use of Patch-Type Sensor Module. Sensors 12(11): 14382-14396 (2012)
2000 – 2009
- 2009
- [c5]Yun-Hee Han, Keun-Chang Kwak:
Combining Global Model and Local Adaptive Neuro-Fuzzy Network. ICIC (2) 2009: 184-189 - 2008
- [c4]Keun-Chang Kwak:
Sound Localization Based on Excitation Source Information for Intelligent Home Service Robots. ICISP 2008: 536-543 - [c3]Keun-Chang Kwak:
Granular-Based Linguistic Models for Identification of Process System. ISICA 2008: 220-227 - 2007
- [c2]Jaeyeon Lee, Do-Hyung Kim, Keun-Chang Kwak, Hye-Jin Kim, Ho-Sub Yoon:
Integrating Evidences of Independently Developed Face and Speaker Recognition Systems by Using Discrete Probability Density Function. RO-MAN 2007: 667-672 - 2006
- [j2]Keun-Chang Kwak, Dong-Hwa Kim:
TSK-Based Linguistic Fuzzy Model with Uncertain Model Output. IEICE Trans. Inf. Syst. 89-D(12): 2919-2923 (2006) - [c1]Keun-Chang Kwak, Do-Hyung Kim, ByoungYoul Song, Daeha Lee, Soo-Young Chi, Young-Jo Cho:
Vision-based Human-Robot Interaction Components for URC Intelligent Service Robots. IROS 2006 - 2005
- [j1]Keun-Chang Kwak, Dong-Hwa Kim:
Adaptive Neuro-Fuzzy Networks with the Aid of Fuzzy Granulation. IEICE Trans. Inf. Syst. 88-D(9): 2189-2196 (2005)
Coauthor Index
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