Jongmyon Kim
Jongmyon Kim
울산대 IT융합학부 교수
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Cited by
Cited by
Reliable fault diagnosis for low-speed bearings using individually trained support vector machines with kernel discriminative feature analysis
M Kang, J Kim, JM Kim, ACC Tan, EY Kim, BK Choi
IEEE Transactions on Power Electronics 30 (5), 2786-2797, 2014
Time-varying and multiresolution envelope analysis and discriminative feature analysis for bearing fault diagnosis
M Kang, J Kim, LM Wills, JM Kim
IEEE Transactions on Industrial Electronics 62 (12), 7749-7761, 2015
Fire flame detection in video sequences using multi-stage pattern recognition techniques
TX Truong, JM Kim
Engineering Applications of Artificial Intelligence 25 (7), 1365-1372, 2012
An effective four-stage smoke-detection algorithm using video images for early fire-alarm systems
TX Tung, JM Kim
Fire Safety Journal 46 (5), 276-282, 2011
Automated irrigation system using solar power
J Uddin, SMT Reza, Q Newaz, J Uddin, T Islam, JM Kim
2012 7th International Conference on Electrical and Computer Engineering …, 2012
Overview of KSTAR initial operation
M Kwon, YK Oh, HL Yang, HK Na, YS Kim, JG Kwak, WC Kim, JY Kim, ...
Nuclear Fusion 51 (9), 094006, 2011
A hybrid feature selection scheme for reducing diagnostic performance deterioration caused by outliers in data-driven diagnostics
M Kang, MR Islam, J Kim, JM Kim, M Pecht
IEEE Transactions on Industrial Electronics 63 (5), 3299-3310, 2016
Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm
M Kang, J Kim, JM Kim
Information Sciences 294, 423-438, 2015
Singular value decomposition based feature extraction approaches for classifying faults of induction motors
M Kang, JM Kim
Mechanical Systems and Signal Processing 41 (1-2), 348-356, 2013
An FPGA-based multicore system for real-time bearing fault diagnosis using ultrasampling rate AE signals
M Kang, J Kim, JM Kim
IEEE Transactions on Industrial Electronics 62 (4), 2319-2329, 2014
A hybrid feature model and deep-learning-based bearing fault diagnosis
M Sohaib, CH Kim, JM Kim
Sensors 17 (12), 2876, 2017
An overview of KSTAR results
JG Kwak, YK Oh, HL Yang, KR Park, YS Kim, WC Kim, JY Kim, SG Lee, ...
Nuclear Fusion 53 (10), 104005, 2013
Robust condition monitoring of rolling element bearings using de-noising and envelope analysis with signal decomposition techniques
P Nguyen, M Kang, JM Kim, BH Ahn, JM Ha, BK Choi
Expert Systems with Applications 42 (22), 9024-9032, 2015
A hybrid technique for medical image segmentation
A Nyma, M Kang, YK Kwon, CH Kim, JM Kim
Journal of Biomedicine and Biotechnology 2012, 2012
A new audio watermarking system using discrete fourier transform for copyright protection
PK Dhar, MI Khan, J Kim
International journal of computer science and network security 10 (6), 35-40, 2010
A hybrid prognostics technique for rolling element bearings using adaptive predictive models
W Ahmad, SA Khan, JM Kim
IEEE Transactions on Industrial Electronics 65 (2), 1577-1584, 2017
A generalized spatial fuzzy c-means algorithm for medical image segmentation
H Van Lung, JM Kim
2009 IEEE International Conference on Fuzzy Systems, 409-414, 2009
Adaptive ECG denoising using genetic algorithm-based thresholding and ensemble empirical mode decomposition
P Nguyen, JM Kim
Information Sciences 373, 499-511, 2016
Learning on demand-a hybrid synchronous/asynchronous approach
H Latchman, C Salzmann, D Gillet, J Kim
IEEE Transactions on Education 44 (2), 17 pp., 2001
Discriminant feature distribution analysis-based hybrid feature selection for online bearing fault diagnosis in induction motors
R Islam, SA Khan, J Kim
Journal of Sensors 2016, 2016
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