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PUBLICATIONS

(Google Scholar Citations)

(Scoups Citations)

Refereed Journal Papers

  1. L. S. Cui, X. Z. Zhang, A.K. Qin, T. Sellis and L. F. Wu, "CDS: Collaborative distant supervision for Twitter account classification", accepted by Expert Systems With Applications, 2017.

  2. J. Liu, M. Gong, A. K. Qin, P. Zhang, ¡°A deep convolutional coupling network for change detection based on heterogeneous optical and radar images,¡± accepted by IEEE Transactions on Neural Networks and Learning Systems, 2016. (2015 SCI 5-years IF: 5.167)

  3. C. Zhang, P. Lim, A. K. Qin and K. C. Tan, ¡°Multi-objective deep belief networks ensemble for remaining useful life estimation in prognostics,¡± accepted by IEEE Transactions on Neural Networks and Learning Systems, 2016. (2015 SCI 5-years IF: 5.167)

  4. X. L. Liang, A. K. Qin, K. Tang and K. C. Tan, ¡°QoS-aware web service composition with internal complementarity,¡± accepted by IEEE Transactions on Services Computing, 2016. (2015 SCI 5-years IF: 3.328)

  5. S. K. Mistry, A. Bouguettaya, H. Dong and A. K. Qin, ¡°Metaheuristic optimization for long-term IaaS service composition,¡± accepted by IEEE Transactions on Services Computing, 2016. (2015 SCI 5-years IF: 3.328)

  6. K. Y. Lu, S. Y. Xia, J. K. Zhang, A. K. Qin, ¡°Robust road detection in shadow conditions,¡± accepted by Journal of Electrical Imaging, 2016 (2015 SCI 5-years IF: 0.840)

  7. B. Y. Qu, B. F. Lang, J. J. Liang, A. K. Qin and O. D. Crisalle, ¡°Two-hidden-layer extreme learning machine for regression and classification,¡± Neurocomputing, 175: 826-834, 2016. (2015 SCI 5-years IF: 2.471)

  8. M. Gong, Y. Wu, Q. Cai, W. Ma, A. K. Qin, Z. Wang and L. Jiao, ¡°Discrete particle swarm optimization for high-order graph matching,¡± Information Sciences, 328: 158-171, 2016. (2015 SCI 5-years IF: 3.683)

  9. L. Wan, K. Tang, M. Li, Y. Zhong and A. K. Qin, ¡°Collaborative active and semi-supervised learning for hyperspectral remote sensing image classification,¡± IEEE Transactions on Geoscience and Remote Sensing, 53(5): 2384-2396, 2015. (2015 SCI 5-years IF: 3.863)

  10. Y. Xiao, Z.-Y. Wang, J. Li, Z.-L. Yuan and A. K. Qin, ¡°Two-step beveled UWB printed monopole antenna with band-notch,¡± International Journal of Antennas and Propagation, 2014. (2015 SCI 5-years IF: 0.751)

  11. S. J. Guo, S.-U. Guan, W. F. Li, K. L. Man, F. Liu and A. K. Qin, ¡°Input space partitioning for neural network learning,¡± International Journal of Applied Evolutionary Computation, 4(2): 56-66, 2013.

  12. P. Yu, A. K. Qin and D. A. Clausi, ¡°Feature extraction of dual-pol SAR imagery for sea-ice image segmentation,¡± Canadian Journal of Remote Sensing, 38(3): 352-366, 2012. (2015 SCI 5-years IF: 1.741)

  13. P. Yu, A. K. Qin and D. A. Clausi, ¡°Unsupervised polarimetric SAR image segmentation and classification using region growing with edge penalty,¡± IEEE Transactions on Geoscience & Remote Sensing, 50(4): 1302-1317, 2012. (2015 SCI 5-years IF: 3.863)

  14. A. K. Qin and D. A. Clausi, ¡°Multivariate image segmentation based on semantic region growing with adaptive edge penalty,¡± IEEE Transactions on Image Processing, 19(8): 2157-2170, 2010. (2015 SCI 5-years IF: 4.786)

  15. D. A. Clausi, A. K. Qin, M. S. Chowdhury, P. Yu and P. Maillard, ¡°MAGIC: MAp-guided ice classification system,¡± Canadian Journal of Remote Sensing, 36(1): S13-S25, 2010. (2015 SCI 5-years IF: 1.741)

  16. A. K. Qin, V. L. Huang and P. N. Suganthan, ¡°Differential evolution with strategy adaptation for global numerical optimization,¡± IEEE Transactions on Evolutionary Computation, 13(2): 398- 417, 2009. (2015 SCI 5-years IF: 6.897; 2012 IEEE Transactions on Evolutionary Computation (TEVC) Outstanding Paper Award; The 4th most-cited IEEE TEVC papers over the last 10 years)

  17. J. J. Liang, A. K. Qin, P. N. Suganthan and S. Baskar, ¡°Comprehensive learning particle swarm optimizer for global optimization of multimodal functions,¡± IEEE Transactions on Evolutionary Computation, 10(3): 281- 295, 2006. (2015 SCI 5-years IF: 6.897; The 1st most-cited IEEE TEVC papers over the last 10 years)

  18. A. K. Qin, P. N. Suganthan and M. Loog, ¡°Generalized null space uncorrelated Fisher discriminant analysis for linear dimensionality reduction,¡± Pattern Recognition, 39(9): 1805-1808, 2006. (2015 SCI 5-years IF: 3.707)

  19. J. J. Liang, S. Baskar, P. N. Suganthan and A. K. Qin, ¡°Performance evaluation of multiagent genetic algorithm,¡± Natural Computing, 5(1): 83-96, 2006. (2015 SCI 5-year IF: 1.019)

  20. Qin-Yu Zhu, A. K. Qin, P. N. Suganthan and Guang-Bin Huang, ¡°Evolutionary extreme learning machine,¡± Pattern Recognition, 38(10): 1759-1763, 2005. (2015 SCI 5-years IF: 3.707)

  21. A. K. Qin and P. N. Suganthan, ¡°Enhanced neural gas network for prototype based clustering,¡± Pattern Recognition, 38(8): 1275-1288, 2005. (2015 SCI 5-years IF: 3.707)

  22. A. K. Qin and P. N. Suganthan, ¡°Initialization insensitive LVQ algorithm based on dynamic cost function adaptation,¡± Pattern Recognition, 38(5): 774-776, 2005. (2015 SCI 5-years IF: 3.707)

  23. A. K. Qin, P. N. Suganthan and M. Loog, ¡°Uncorrelated heteroscedastic LDA algorithm based on the weighted pairwise Chernoff criterion,¡± Pattern Recognition, 38(4): 613-616, 2005. (2015 SCI 5-years IF: 3.707)

  24. E. K. Tang, P. N. Suganthan, X. Yao and A. K. Qin, ¡°Linear dimensionality reduction using relevance weighted LDA,¡± Pattern Recognition, 38(4): 485-493, 2005. (2015 SCI 5-years IF: 3.707)

  25. A. K. Qin and P. N. Suganthan, ¡°Robust growing neural gas algorithm with application in cluster analysis,¡± Neural Networks, 17 (8-9): 1135-1148, 2004. (2015 SCI 5-years IF: 2.890)

Refereed Conference Papers

  1. C. Jin and and A. K. Qin, ¡°A GPU-based implementation of brain storm optimization¡±, accepted by 2017 IEEE Congress on Evolutionary Computation (CEC¡¯17 ), Donostia-San Sebasti¨¢n, Spain, June 5-8, 2017.

  2. J. Liono, A. K. Qin and F. D. Salim, ¡°Optimal time window for temporal segmentation of sensor streams in multi-activity recognition,¡± Proc. of the 13th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous¡¯16), Hiroshima, Japan, November 28-December 1, 2016.

  3. J. K. Zhang, S. Y. Xia, H. Pan and A. K. Qin, ¡°A genetics-motivated unsupervised model for tri-subject kinship verification,¡± Proc. of the 23rd IEEE International Conference on Image Processing (ICIP¡¯16), Phoenix, Arizona, USA, September 25¨C28, 2016.

  4. J. K. Zhang, S. Y. Xia, K. Y. Lu, H. Pan and A. K. Qin, ¡°Robust road detection from a single image,¡± Proc. of the 23rd International Conference on Pattern Recognition (ICPR¡¯16), Cancun, Mexico, December 4-8, 2016.

  5. A. Campbell, V. Ciesielski and A. K. Qin, ¡°Node label matching improves classification performance in deep belief networks,¡± Proc. of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN¡¯16), Vancouver, Canada, July 25-29, 2016.

  6. Y. W. Li, L. Z. Jin, A. K. Qin, C. Y. Sun, Y. S. Ong and T. Cui, ¡°Semi-supervised auto-encoder based on manifold learning,¡± Proc. of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN¡¯16), Vancouver, Canada, July 25-29, 2016.

  7. H. Song, A. K. Qin and F. D. S. Salim, ¡°Multivariate electricity consumption prediction with extreme learning machine,¡± Proc. of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN¡¯16), Vancouver, Canada, July 25-29, 2016.

  8. A. Kenny, X. D. Li, A. K. Qin and A. T. Ernst, ¡°A population-based local search technique with random descent and jump for the steiner tree problem in graphs,¡± Proc. of the 2016 Genetic and Evolutionary Computation Conference (GECCO¡¯16), Denver, Colorado, USA, July 20-24, 2016.

  9. R. Chen, H. R. Li, A. K. Qin, S. Kasiviswanathan and H. X. Jin, ¡°Private spatial data aggregation in the local setting,¡± Proc. of the 32nd IEEE International Conference on Data Engineering (ICDE¡¯16), Helsinki, Finland, May 16-20, 2016.

  10. S. Xia, J. K. Zhang, K. Y. Lu and A. K. Qin, ¡°Road detection via unsupervised feature learning,¡± Proc. of the 30th International Conference on Image and Vision Computing New Zealand (IVCNZ¡¯15), Auckland, New Zealand, November 23-24, 2015.

  11. S. Mistry, A. Bouguettaya, H. Dong and A. K. Qin, ¡°Economic model based genetic optimization for long-term IaaS service composition,¡± Proc. of the 13th International Conference on Service Oriented Computing (ICSOC¡¯15), Goa, India, November 16-19, 2015.

  12. S. Mistry, A. Bouguettaya, H. Dong and A. K. Qin, ¡°Predicting and optimizing dynamic behavior of consumer requests in long-term IaaS service composition," Proc. of the 22nd IEEE International Conference on Web Services (ICWS¡¯15), New York, USA, June 27-July 2, 2015.

  13. B. Kazimipour, M. Omidvar, X. Li and A. K. Qin, ¡°A sensitivity study of contribution-based cooperative co-evolutionary algorithms,¡± Proc. of the 2015 IEEE Congress on Evolutionary Computation (CEC¡¯15), Sendai, Japan, May 25-28, 2015.

  14. S. C. Liu, Y. F. Wei, K. Tang, A. K. Qin and X. Yao, ¡°QoS-aware long-term based service composition in cloud computing,¡± Proc. of the 2015 IEEE Congress on Evolutionary Computation (CEC¡¯15), Sendai, Japan, May 25-28, 2015.

  15. C. Jin, A. K. Qin and K. Tang, ¡°Local ensemble surrogate assisted crowding differential evolution,¡± Proc. of the 2015 IEEE Congress on Evolutionary Computation (CEC¡¯15), Sendai, Japan, May 25-28, 2015.

  16. Allan Campbell, Vic Ciesielski and A. K. Qin, ¡°Feature discovery by deep learning for aesthetic analysis of evolved abstract images¡±, Proc. of Evostar 2015, Copenhagen, Denmark, April 8-10, 2015.

  17. B. Kazimipour, X. Li and A. K. Qin, ¡°Why advanced population initialization techniques perform poorly in high dimensions?¡± Proc. of the 10th International Conference on Simulated Evolution and Learning (SEAL¡¯14), Dunedin, New Zealand, December 15-18, 2014.

  18. P. Yang, K. Tang, L. Li and A. K. Qin, ¡°Evolutionary Robust Optimization with Multiple Solutions,¡± Proc. of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES¡¯14), Singapore, November 10-12, 2014.

  19. T. H. Wong, A. K. Qin, S. Wang and Y. Shi, ¡°cuSaDE: A CUDA-based Parallel Self-adaptive Differential Evolution Algorithm,¡± Proc. of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES¡¯14), Singapore, November 10-12, 2014. (Outstanding Overall Paper Award)

  20. J. J. Liang, H. Song, B. Y. Qu, W. Liu, and A. K. Qin, ¡°Neural Network Based on Dynamic Multi-Swarm Particle Swarm Optimizer for Ultra-Short-Term Load Forecasting,¡± Proc. of the 5th International Conference on Swarm Intelligence (ICSI¡¯14), Hefei, China, October 17-20, 2014.

  21. A. K. Qin, K. Tang, Hong Pan and Si-Yu Xia, ¡°Self-adaptive differential evolution with local search chains for real-parameter single-objective optimization,¡± Proc. of the 2014 IEEE Congress on Evolutionary Computation (CEC¡¯14), Beijing, China, July 6-11, 2014.

  22. B. Xue, A. K. Qin and M. Zhang, ¡°An archive based particle swarm optimization for feature selection in classification,¡± Proc. of the 2014 IEEE Congress on Evolutionary Computation (CEC¡¯14), Beijing, China, July 6-11, 2014.

  23. B. Kazimipour, Xiaodong Li, A. K. Qin, ¡°A review of population initialization techniques for evolutionary algorithms,¡± Proc. of the 2014 IEEE Congress on Evolutionary Computation (CEC¡¯14), Beijing, China, July 6-11, 2014.

  24. B. Kazimipour, M. N. Omidvar, Xiaodong Li, A. K. Qin, ¡°A novel hybridization of opposition-based learning and cooperative co-evolutionary for large-scale optimization,¡± Proc. of the 2014 IEEE Congress on Evolutionary Computation (CEC¡¯14), Beijing, China, July 6-11, 2014.

  25. B. Kazimipour, Xiaodong Li and A. K. Qin, ¡°Effects of population initialization on differential evolution for large scale optimization,¡± Proc. of the 2014 IEEE Congress on Evolutionary Computation (CEC¡¯14), Beijing, China, July 6-11, 2014.

  26. J. Zhong, K. Tang and A. K. Qin, ¡°Finding convex hull vertices in metric space,¡± Proc. of the 2014 IEEE International Joint Conference on Neural Networks (IJCNN¡¯14), Beijing, China, July 6-11, 2014.

  27. Si-Yu Xia, Hong Pan and A. K. Qin, ¡°Face clustering in photo album,¡± Proc. of the 22nd International Conference on Pattern Recognition (ICPR¡¯14), Stockholm, Sweden, August 24-28, 2014.

  28. W. Liu, H. Song, J. J. Liang, B. Y. Qu, A. K. Qin, ¡°Neural Network Based on Self-adaptive Differential Evolution for Ultra-Short-Term Power Load Forecasting,¡± Proc. of the 10th International Conference on Intelligent Computing (ICIC¡¯14), Taiyuan, China, August 3-6, 2014.

  29. A. K. Qin and Xiaodong Li, ¡°Differential evolution on the CEC-2013 single-objective continuous optimization testbed,¡± Proc. of the 2013 IEEE Congress on Evolutionary Computation (CEC¡¯13), Cancun, Mexico, June 20-23, 2013.

  30. Feng Xie, A. K. Qin, Andy Song and Vic Ciesielski, ¡°Sensor-based activity recognition with improved GP-based classifier,¡± Proc. of the 2013 IEEE Congress on Evolutionary Computation (CEC¡¯13), Cancun, Mexico, June 20-23, 2013.

  31. Borhan Kazimipour, Xiaodong Li and A. K. Qin, ¡°Initialization methods for large scale global optimization,¡± Proc. of the 2013 IEEE Congress on Evolutionary Computation (CEC¡¯13), Cancun, Mexico, June 20-23, 2013.

  32. A. K. Qin and Xiaodong Li, ¡°Investigation of self-adaptive differential evolution on the CEC-2013 single-objective continuous optimization testbed,¡± Proc. of the 2013 IEEE Congress on Evolutionary Computation (CEC¡¯13), Cancun, Mexico, June 20-23, 2013.

  33. Hong Pan, Yaping Zhu, A. K. Qin and Liangzheng Xia, ¡°Mining heterogeneous class-specific codebook for categorical object detection and classification,¡± Proc. of the 2013 IEEE International Conference on Image Processing (ICIP¡¯13), Melbourne, Australia, September 15-18, 2013.

  34. Hong Pan, Yaping Zhu, Si-Yu Xia and K. Qin, ¡°Improved generic categorical object detection Fusing depth cue with 2D appearance and shape features,¡± Proc. of the 21st International Conference on Pattern Recognition (ICPR¡¯12), Tsukuba Science City, Japan, November, 2012.

  35. A. K. Qin, F. Raimondo, F. Forbes and Y. S. Ong, ¡°An improved CUDA-based implementation of differential evolution on GPU,¡± Proc. of the 2012 Genetic and Evolutionary Computation Conference (GECCO¡¯12), Philadelphia, USA, July, 2012. (Best Paper Nomination)

  36. A. K. Qin and F. Forbes, ¡°Dynamic regional harmony search with opposition and local learning,¡± Proc. of the 2011 Genetic and Evolutionary Computation Conference (GECCO¡¯11), Dublin, Ireland, July, 2011.

  37. A. K. Qin and F. Forbes, ¡°Harmony search with differential mutation based pitch adjustment,¡± Proc. of the 2011 Genetic and Evolutionary Computation Conference (GECCO¡¯11), Dublin, Ireland, July, 2011.

  38. D. A. Clausi, A. K. Qin, M. S. Chowdhury, P. Yu and P. Maillard, ¡°MAGIC: MAp-Guided Ice Classification system for operational analysis,¡± Proc. of the 5th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS¡¯08) in conjunction with the 19th International Conference on Pattern Recognition (ICPR¡¯08), Tampa, Florida, USA, December 7, 2008.

  39. V. L. Huang, A. K. Qin and P. N. Suganthan, ¡°Multi-objective optimization based on self-adaptive differential evolution algorithm,¡± Proc. of the 2007 IEEE Congress on Evolutionary Computation (CEC¡¯07), Singapore, September 2007.

  40. A. K. Qin, P. N. Suganthan, C. H. Tay and H. S. Pa, ¡°Personal identification system based on multiple palmprint features,¡± Proc. of the 9th International Conference on Control, Automation, Robotics and Vision (ICARCV¡¯06), Singapore, December, 2006.

  41. A. K. Qin, P. N. Suganthan and M. Loog, ¡°Efficient feature extraction based on regularized uncorrelated Chernoff discriminant analysis,¡± Proc. of the 18th Internatinal Conference on Pattern Recognition (ICPR¡¯06), Hong Kong, China, August 2006.

  42. V. L. Huang, A. K. Qin and P. N. Suganthan, ¡°Self-adaptive differential evolution algorithm for constrained real-parameter optimization,¡± Proc. of the 2006 IEEE Congress on Evolutionary Computation (CEC¡¯06), Vancouver, BC, Canada, July 2006.

  43. A. K. Qin and P. N. Suganthan, ¡°Self-adaptive differential evolution algorithm for numerical optimization,¡± Proc. of the 2005 IEEE Congress on Evolutionary Computation (CEC¡¯05), Edinburgh, UK, September 2005.

  44. A. K. Qin, S. Y. M. Shi, P. N. Suganthan and M. Loog, ¡°Enhanced direct linear discriminant analysis for feature extraction on high dimensional data,¡± Proc. of the 20th National Conference on Artificial Intelligence (AAAI¡¯05), Pittsburgh, Pennsylvania, USA, July 2005.

  45. J. J. Liang, A. K. Qin, P. N. Suganthan and S. Baskar, ¡°Evaluation of comprehensive learning particle swarm optimizer,¡± Proc. of the 11th International Conference on Neural Information Processing (ICONIP¡¯04), pp. 230-235, Science City, Calcutta, November 2004.

  46. J. J. Liang, A. K. Qin, P. N. Suganthan and S. Baskar, ¡°Particle swarm optimization algorithms with novel learning strategies,¡± Proc. of the 2004 IEEE International Conference on Systems, Man and Cybernetics 2004 (SMC¡¯04), Hague, Netherlands, October 2004.

  47. A. K. Qin, P. N. Suganthan and J. J. Liang, ¡°A new generalized LVQ algorithm via harmonic to minimum distance measure transition,¡± Proc. of the 2004 IEEE International Conference on Systems, Man and Cybernetics 2004 (SMC¡¯04), Hague, Netherlands, October 2004.

  48. A. K. Qin and P. N. Suganthan, ¡°A novel kernel prototype-based learning algorithm,¡± Proc. of the 17th International Conference on Pattern Recognition (ICPR¡¯04), Cambridge, UK, August 2004.

  49. A. K. Qin and P. N. Suganthan, ¡°Kernel neural gas algorithms with application to cluster analysis,¡± Proc. of the 17th International Conference on Pattern Recognition (ICPR¡¯04), Cambridge, UK, August 2004.

  50. A. K. Qin and P. N. Suganthan, ¡°Growing generalized learning vector quantization with local neighborhood adaptation rule,¡± Proc. of the 2004 IEEE International Conference on Intelligent Systems (ICIS¡¯04), Sofia, Bulgaria, June 2004.

  51. A. K. Qin and P. N. Suganthan, ¡°A robust neural gas algorithm for clustering analysis,¡± Proc. of the International Conference on Intelligent Sensing and Information Processing (ICISIP¡¯04), Chennai, India, January 2004.

Other Articles

  1. X. Li, K. Tang, M. Omidvar, Z. Yang and K. Qin, ¡°Benchmark Functions for the CEC¡¯2013 Special Session and Competition on Large Scale Global Optimization,¡± Technical Report, Evolutionary Computation and Machine Learning Group, RMIT University, Australia, 2013.

  2. V. L. Huang, A. K. Qin, K. Deb, E. Zitzler, P. N. Suganthan, J. J .Liang, M. Preuss and S. Huband, ¡°Problem definitions for performance assessment of multi-objective optimization algorithms,¡± Special Session & Competition on Performance Assessment of Multi-Objective Optimization Algorithms for IEEE Congress on Evolutionary Computation (CEC¡¯07), Singapore, Technical Report, Nanyang Technological University, Singapore, 2007.

  3. V. L. Huang, P. N. Suganthan, A. K. Qin and S. Baskar, ¡°Multi-objective differential evolution with external archive and harmonic distance-based diversity measure,¡± Technical Report, Nanyang Technological University, 2005.