| Ensemble with neural networks for bankruptcy prediction MJ Kim, DK Kang Expert systems with applications 37 (4), 3373-3379, 2010 | 327 | 2010 |
| Learning classifiers for misuse and anomaly detection using a bag of system calls representation DK Kang, D Fuller, V Honavar Proceedings from the Sixth Annual IEEE SMC Information Assurance Workshop …, 2005 | 228 | 2005 |
| Geometric mean based boosting algorithm with over-sampling to resolve data imbalance problem for bankruptcy prediction MJ Kim, DK Kang, HB Kim Expert Systems with Applications 42 (3), 1074-1082, 2015 | 212 | 2015 |
| Biased dropout and crossmap dropout: learning towards effective dropout regularization in convolutional neural network A Poernomo, DK Kang Neural networks 104, 60-67, 2018 | 133 | 2018 |
| Classifiers selection in ensembles using genetic algorithms for bankruptcy prediction MJ Kim, DK Kang Expert Systems with applications 39 (10), 9308-9314, 2012 | 114 | 2012 |
| Learning accurate and concise naïve Bayes classifiers from attribute value taxonomies and data J Zhang, DK Kang, A Silvescu, V Honavar Knowledge and information systems 9, 157-179, 2006 | 83 | 2006 |
| Learning classifiers for misuse detection using a bag of system calls representation DK Kang, D Fuller, V Honavar Intelligence and Security Informatics: IEEE International Conference on …, 2005 | 51 | 2005 |
| Generation of attribute value taxonomies from data for data-driven construction of accurate and compact classifiers DK Kang, A Silvescu, J Zhang, V Honavar Fourth IEEE International Conference on Data Mining (ICDM'04), 130-137, 2004 | 31* | 2004 |
| Experimental analysis of naïve Bayes classifier based on an attribute weighting framework with smooth kernel density estimations ZL Xiang, XR Yu, DK Kang Applied Intelligence 44, 611-620, 2016 | 30 | 2016 |
| Anomaly detection of water level using deep autoencoder IT Nicholaus, JR Park, K Jung, JS Lee, DK Kang Sensors 21 (19), 6679, 2021 | 27 | 2021 |
| Multinomial event model based abstraction for sequence and text classification DK Kang, J Zhang, A Silvescu, V Honavar Abstraction, Reformulation and Approximation: 6th International Symposium …, 2005 | 24 | 2005 |
| Learning decision trees with taxonomy of propositionalized attributes DK Kang, K Sohn Pattern Recognition 42 (1), 84-92, 2009 | 23 | 2009 |
| A novel diminish smooth L1 loss model with generative adversarial network AR Sutanto, DK Kang Intelligent Human Computer Interaction: 12th International Conference, IHCI …, 2021 | 22 | 2021 |
| One-class naïve Bayes with duration feature ranking for accurate user authentication using keystroke dynamics J Ho, DK Kang Applied Intelligence 48, 1547-1564, 2018 | 22 | 2018 |
| Mini-batch bagging and attribute ranking for accurate user authentication in keystroke dynamics J Ho, DK Kang Pattern Recognition 70, 139-151, 2017 | 21 | 2017 |
| Cascade of one class classifiers for water level anomaly detection FHS Tan, JR Park, K Jung, JS Lee, DK Kang Electronics 9 (6), 1012, 2020 | 20 | 2020 |
| Analysis of human factors in software application design for effective user experience S Abduljalil, DK Kang 13th International Conference on Advanced Communication Technology …, 2011 | 18 | 2011 |
| TRIPPER: Rule learning using taxonomies F Vasile, A Silvescu, DK Kang, V Honavar Advances in Knowledge Discovery and Data Mining: 10th Pacific-Asia …, 2006 | 17 | 2006 |
| A review on dropout regularization approaches for deep neural networks within the scholarly domain I Salehin, DK Kang Electronics 12 (14), 3106, 2023 | 15 | 2023 |
| Trainable activation function with differentiable negative side and adaptable rectified point K Pratama, DK Kang Applied Intelligence 51 (3), 1784-1801, 2021 | 15 | 2021 |
Sami Abduljalil Abdulhak NajiPostdoc @Gent UniversityGeverifieerd e-mailadres voor vib-ugent.be
