Variational autoencoder based anomaly detection using reconstruction probability J An, S Cho Special lecture on IE 2 (1), 1-18, 2015 | 1951 | 2015 |
KoNLPy: Korean natural language processing in Python EL Park, S Cho Annual Conference on Human and Language Technology, 133-136, 2014 | 373 | 2014 |
Web-based keystroke dynamics identity verification using neural network S Cho, C Han, DH Han, HI Kim Journal of organizational computing and electronic commerce 10 (4), 295-307, 2000 | 314 | 2000 |
EUS SVMs: Ensemble of under-sampled SVMs for data imbalance problems P Kang, S Cho International conference on neural information processing, 837-846, 2006 | 247 | 2006 |
Bag-of-concepts: Comprehending document representation through clustering words in distributed representation HK Kim, H Kim, S Cho Neurocomputing 266, 336-352, 2017 | 246 | 2017 |
System and method for performing user authentication based on user behavior patterns S Cho, M Jang US Patent App. 11/651,132, 2007 | 223 | 2007 |
Keystroke dynamics identity verification—its problems and practical solutions E Yu, S Cho Computers & Security 23 (5), 428-440, 2004 | 223 | 2004 |
Apparatus for authenticating an individual based on a typing pattern by using a neural network system SZ Cho, DH Han US Patent 6,151,593, 2000 | 199 | 2000 |
Rainfall prediction using artificial neural networks S Lee, S Cho, PM Wong journal of geographic information and Decision Analysis 2 (2), 233-242, 1998 | 167 | 1998 |
Keystroke dynamics-based authentication for mobile devices S Hwang, S Cho, S Park Computers & Security 28 (1-2), 85-93, 2009 | 164 | 2009 |
GA-SVM wrapper approach for feature subset selection in keystroke dynamics identity verification E Yu, S Cho Proceedings of the International Joint Conference on Neural Networks, 2003 …, 2003 | 153 | 2003 |
A virtual metrology system for semiconductor manufacturing P Kang, H Lee, S Cho, D Kim, J Park, CK Park, S Doh Expert Systems with Applications 36 (10), 12554-12561, 2009 | 151 | 2009 |
Detecting financial misstatements with fraud intention using multi-class cost-sensitive learning YJ Kim, B Baik, S Cho Expert systems with applications 62, 32-43, 2016 | 149 | 2016 |
Machine learning-based novelty detection for faulty wafer detection in semiconductor manufacturing D Kim, P Kang, S Cho, H Lee, S Doh Expert Systems with Applications 39 (4), 4075-4083, 2012 | 141 | 2012 |
Virtual metrology for run-to-run control in semiconductor manufacturing P Kang, D Kim, H Lee, S Doh, S Cho Expert Systems with Applications 38 (3), 2508-2522, 2011 | 141 | 2011 |
Response models based on bagging neural networks K Ha, S Cho, D MacLachlan Journal of Interactive Marketing 19 (1), 17-30, 2005 | 139 | 2005 |
Champion-challenger analysis for credit card fraud detection: Hybrid ensemble and deep learning E Kim, J Lee, H Shin, H Yang, S Cho, S Nam, Y Song, J Yoon, J Kim Expert Systems with Applications 128, 214-224, 2019 | 138 | 2019 |
Response modeling with support vector machines HJ Shin, S Cho Expert Systems with applications 30 (4), 746-760, 2006 | 136 | 2006 |
Keystroke dynamics-based user authentication using long and free text strings from various input devices P Kang, S Cho Information Sciences 308, 72-93, 2015 | 133 | 2015 |
Continual retraining of keystroke dynamics based authenticator P Kang, S Hwang, S Cho Advances in Biometrics: International Conference, ICB 2007, Seoul, Korea …, 2007 | 131 | 2007 |