| Constructing support vector machine ensemble HC Kim, S Pang, HM Je, D Kim, SY Bang Pattern recognition 36 (12), 2757-2767, 2003 | 695 | 2003 |
| Incremental linear discriminant analysis for classification of data streams S Pang, S Ozawa, N Kasabov IEEE transactions on Systems, Man, and Cybernetics, part B (Cybernetics) 35 …, 2005 | 441 | 2005 |
| Privacy-aware data fusion and prediction with spatial-temporal context for smart city industrial environment L Qi, C Hu, X Zhang, MR Khosravi, S Sharma, S Pang, T Wang IEEE Transactions on Industrial Informatics 17 (6), 4159-4167, 2020 | 244 | 2020 |
| Support vector machine ensemble with bagging HC Kim, S Pang, HM Je, D Kim, SY Bang Pattern Recognition with Support Vector Machines: First International …, 2002 | 166 | 2002 |
| Incremental learning of chunk data for online pattern classification systems S Ozawa, S Pang, N Kasabov IEEE Transactions on Neural Networks 19 (6), 1061-1074, 2008 | 139 | 2008 |
| Incremental learning of feature space and classifier for face recognition S Ozawa, SL Toh, S Abe, S Pang, N Kasabov Neural Networks 18 (5-6), 575-584, 2005 | 126 | 2005 |
| Face membership authentication using SVM classification tree generated by membership-based LLE data partition S Pang, D Kim, SY Bang IEEE transactions on Neural networks 16 (2), 436-446, 2005 | 111 | 2005 |
| Pattern classification using support vector machine ensemble HC Kim, S Pang, HM Je, D Kim, SY Bang 2002 International Conference on Pattern Recognition 2, 160-163, 2002 | 106 | 2002 |
| Membership authentication in the dynamic group by face classification using SVM ensemble S Pang, D Kim, SY Bang Pattern Recognition Letters 24 (1-3), 215-225, 2003 | 92 | 2003 |
| Transductive support vector machines and applications in bioinformatics for promoter recognition N Kasabov, S Pang International Conference on Neural Networks and Signal Processing, 2003 …, 2003 | 81 | 2003 |
| Referential kNN Regression for Financial Time Series Forecasting T Ban, R Zhang, S Pang, A Sarrafzadeh, D Inoue Neural Information Processing: 20th International Conference, ICONIP 2013 …, 2013 | 79 | 2013 |
| A modified incremental principal component analysis for on-line learning of feature space and classifier S Ozawa, S Pang, N Kasabov Pacific Rim International Conference on Artificial Intelligence, 231-240, 2004 | 51 | 2004 |
| Classification consistency analysis for bootstrapping gene selection S Pang, I Havukkala, Y Hu, N Kasabov Neural Computing and Applications 16, 527-539, 2007 | 49 | 2007 |
| Diversified and scalable service recommendation with accuracy guarantee L Wang, X Zhang, T Wang, S Wan, G Srivastava, S Pang, L Qi IEEE Transactions on Computational Social Systems 8 (5), 1182-1193, 2020 | 46 | 2020 |
| Inductive vs transductive inference, global vs local models: SVM, TSVM, and SVMT for gene expression classification problems S Pang, N Kasabov 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No …, 2004 | 42 | 2004 |
| Personalized mode transductive spanning SVM classification tree S Pang, T Ban, Y Kadobayashi, N Kasabov Information Sciences 181 (11), 2071-2085, 2011 | 41 | 2011 |
| Urban air pollution alert service for smart cities SR Garzon, S Walther, S Pang, B Deva, A Küpper Proceedings of the 8th International Conference on the Internet of Things, 1-8, 2018 | 37 | 2018 |
| Crop monitoring by multimodal remote sensing: A review P Karmakar, SW Teng, M Murshed, S Pang, Y Li, H Lin Remote Sensing Applications: Society and Environment 33, 101093, 2024 | 35 | 2024 |
| The global cyber security workforce: an ongoing human capital crisis L Fourie, S Pang, T Kingston, H Hettema, P Watters, H Sarrafzadeh Global Business and Technology Association, 2014 | 33 | 2014 |
| Dynamic class imbalance learning for incremental LPSVM S Pang, L Zhu, G Chen, A Sarrafzadeh, T Ban, D Inoue Neural Networks 44, 87-100, 2013 | 33 | 2013 |
