Pattern Recognition and Machine Learning Lab

2017

  • Qiang Yang; Wei-Neng Chen; Jeremiah D. Deng; Yun Li; Tianlong Gu; Jun Zhang: A Level-based Learning Swarm Optimizer for Large Scale Optimization, to appear in IEEE Trans. on Evol. Comp. (2017).
  • Qiang Yang, Wei-Neng Chen, Tianlong Gu, Huaxiang Zhang, Jeremiah D. Deng, Yun Li, Jun Zhang: Segment-Based Predominant Learning Swarm Optimizer for Large-Scale Optimization. IEEE Trans. Cybernetics 47(9): 2896-2910 (2017)
  • Qunfeng Liu, Wei-Neng Chen, Jeremiah D. Deng, Tianlong Gu, Huaxiang Zhang, Zhengtao Yu, Jun Zhang: Benchmarking Stochastic Algorithms for Global Optimization Problems by Visualizing Confidence Intervals. IEEE Trans. Cybernetics 47(9): 2924-2937 (2017)
  • Sean Hsin-Shyuan Lee, Jeremiah D. Deng, Lizhi Peng, Martin K. Purvis, Maryam Purvis: Top-k Merit Weighting PBIL for Optimal Coalition Structure Generation of Smart Grids. ICONIP (4) 2017: 171-181
  • Ahmad Shahi, Jeremiah D. Deng, Brendon J. Woodford: Online Hidden Conditional Random Fields to Recognize Activity-Driven Behavior Using Adaptive Resilient Gradient Learning. ICONIP (1) 2017: 515-525
  • Ahmad Shahi, Jeremiah D. Deng, Brendon J. Woodford: A streaming ensemble classifier with multi-class imbalance learning for activity recognition. IJCNN 2017: 3983-3990

2016

  • Jeremiah D. Deng: Online Outlier Detection of Energy Data Streams Using Incremental and Kernel PCA Algorithms. ICDM Workshops 2016: 390-397
  • Xianbin Gu, Jeremiah D. Deng, Martin K. Purvis: A hierarchical segmentation tree for superpixel-based image segmentation. IVCNZ 2016: 1-6
  • Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford, Ahmad Shahi: Online Weighted Clustering for Real-time Abnormal Event Detection in Video Surveillance. ACM Multimedia 2016: 536-540
  • Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford: Shot Boundary Detection Using Multi-instance Incremental and Decremental One-Class Support Vector Machine. PAKDD (1) 2016: 165-176
  • Xianbin Gu, Jeremiah D. Deng, Martin K. Purvis: Image segmentation with superpixel-based covariance descriptors in low-rank representation. CoRR abs/1605.05466 (2016)

2015

  • Munir Shah, Jeremiah D. Deng, Brendon J. Woodford: A Self-adaptive CodeBook (SACB) model for real-time background subtraction. Image Vision Comput. 38: 52-64 (2015)
  • Yuwei Xu, Jeremiah D. Deng, Mariusz Nowostawski, Martin K. Purvis: Optimized routing for video streaming in multi-hop wireless networks using analytical capacity estimation. J. Comput. Syst. Sci. 81(1): 145-157 (2015)
  • Ahmad Shahi, Brendon J. Woodford, Jeremiah D. Deng: Event Classification Using Adaptive Cluster-Based Ensemble Learning of Streaming Sensor Data. Australasian Conference on Artificial Intelligence 2015: 505-516.
  • Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford: Anomaly detection in crowd scenes via online adaptive one-class support vector machines. ICIP 2015: 2434-2438

2014

  • Ashfaqur Rahman, Jeremiah D. Deng, Jiuyong Li (Eds.): Workshop on Machine Learning for Sensory Data Analysis (MLSDA@PRIAI'2014), ACM, 2014, ISBN 978-1-4503-3159-3.
  • Xianbin Gu, Jeremiah D. Deng, Martin K. Purvis, Improving Superpixel-based Image Segmentation by Incorporating Color Covariance Matrix Manifolds. ICIP'14 Paris. (Top 10% paper prize)
  • Adeel Javed, Haibo Zhang, Zhiyi Huang, Jeremiah D. Deng, BWS: Beacon-driven Wake-up Scheme for Train Localization using Wireless Sensor Networks, ICC'14 Sydney.
  • M. Shah, J. D. Deng, B. J. Woodford, Video background modeling: Recent approaches, issues and our proposed techniques, Machine Vision and Applications, 1105-1119, Springer, 2014.

2013

  • G. Guan, Z. Wang, S. Lu, J. D. Deng, D. D. Feng: Keypoint-Based Keyframe Selection. IEEE Trans. Circuits Syst. Video Techn. 23(4): 729-734 (2013)
  • Yuwei Xu, Jeremiah D. Deng, Mariusz Nowostawski, Martin K. Purvis, Optimized Routing for Video Streaming in Multi-hop Wireless Networks using Analytical Capacity Estimation, accepted by Journal of Computer and System Sciences, Elsevier, 2013.
  • Jeremiah D. Deng, Yue Zhang: Light-weight online predictive data aggregation for wireless sensor networks. Workshop on Machine Learning for Sensory Data Analysis (MLSDA@AUS-AI 2013): 35-42, ACM, 2013.
  • Munir Shah, Jeremiah D. Deng, Brendon J. Woodford, Improving Mixture of Gaussians Background Model through adaptive learning and Spatio-Temporal voting, Proc. IEEE Inter. Conf. on Image Processing (ICIP) 2013, 3436-3440.
  • Suet-Peng Yong, Jeremiah D. Deng, Martin K. Purvis: Wildlife video key-frame extraction based on novelty detection in semantic context. Multimedia Tools Appl. 62(2): 359-376 (2013)
  • Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford: Event Detection Using Quantized Binary Code and Spatial-Temporal Locality Preserving Projections. Australasian Conference on Artificial Intelligence 2013: 123-134
  • Munir Shah, Jeremiah D. Deng, Brendon J. Woodford: Growing Neural Gas Video Background Model (GNG-BM). Australasian Conference on Artificial Intelligence 2013: 135-147
  • Femi A. Aderohunmu, Giacomo Paci, Davide Brunelli, Jeremiah D. Deng, Luca Benini, Martin K. Purvis: Trade-offs of Forecasting Algorithm for Extending WSN Lifetime in a Real-World Deployment. DCOSS 2013: 283-285
  • Femi A. Aderohunmu, Giacomo Paci, Davide Brunelli, Jeremiah D. Deng, Luca Benini, Martin K. Purvis: An Application-Specific Forecasting Algorithm for Extending WSN Lifetime. DCOSS 2013: 374-381
  • Yuwei Xu, Jeremiah D. Deng, Mariusz Nowostawski: Quality of service for video streaming over multi-hop wireless networks: Admission control approach based on analytical capacity estimation. Proc. ISSNIP 2013: 345-350
  • Femi A. Aderohunmu, Giacomo Paci, Davide Brunelli, Jeremiah D. Deng, Luca Benini: Prolonging the lifetime of wireless sensor networks using light-weight forecasting algorithms. Proc. ISSNIP 2013: 461-466
  • Femi A. Aderohunmu, Giacomo Paci, Luca Benini, Jeremiah D. Deng, Davide Brunelli: SWIFTNET: A data acquisition protocol for fast-reactive monitoring applications. SIES 2013: 93-96

2012

  • Suet-Peng Yong, Jeremiah D. Deng, Martin K. Purvis: Novelty detection in wildlife scenes through semantic context modelling. Pattern Recognition 45(9): 3439-3450 (2012)
  • Munir Shah, Jeremiah D. Deng, Brendon J. Woodford: Illumination Invariant Background Model Using Mixture of Gaussians and SURF Features. ACCV Workshops (1) 2012: 308-314
  • Yuwei Xu, Jeremiah D. Deng, Mariusz Nowostawski: Optimizing Routing in Multi-hop Wireless Networks Using Analytical Capacity Estimation: A Study on Video Streaming. HPCC-ICESS 2012: 748-755.
  • Femi A. Aderohunmu, Jeremiah D. Deng, Martin K. Purvis: Optimization of Energy-efficient Protocols with Energy-heterogeneity for Coverage Preservation in Wireless Sensor Networks: An Empirical Study. HPCC-ICESS 2012: 1173-1178
  • Suet-Peng Yong, Jeremiah D. Deng, Martin K. Purvis: Key-frame extraction of wildlife video based on semantic context modeling. Proc. IJCNN 2012: 1-8
  • Munir Shah, Jeremiah D. Deng, Brendon J. Woodford: Enhancing the mixture of Gaussians background model with local matching and local adaptive learning. Proc. IVCNZ 2012: 103-108
  • Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford: Video manifold modelling: finding the right parameter settings for anomaly detection. Proc. IVCNZ 2012: 168-173
  • Brendan McCane, Steven Mills, Jeremiah D. Deng (Eds.): Image and Vision Computing New Zealand, IVCNZ '12, Dunedin, New Zealand - November 26 - 28, 2012. ACM 2012, ISBN 978-1-4503-1473-2

2011

  • Femi A. Aderohunmu, Jeremiah D. Deng, Martin K. Purvis: Enhancing Clustering in Wireless Sensor Networks with Energy Heterogeneity. IJBDCN 7(4): 18-31 (2011)
  • Jeremiah D. Deng, Martin K. Purvis: Multi-core application performance optimization using a constrained tandem queueing model. J. Network and Computer Applications 34(6): 1990-1996 (2011)
  • Munir Shah, Jeremiah D. Deng, Brendon J. Woodford: Enhanced Codebook Model for Real-Time Background Subtraction. ICONIP (3) 2011: 449-458

2010 and earlier (selected)

  • Brendon J. Woodford: Automatic optimization of pruning in evolving fuzzy neural networks using an entropy measure. IJCNN 2010: 1-7
  • Jeremiah D. Deng: Controlling Chaotic Associative Memory for Multiple Pattern Retrieval. Cognitive Computation 2(4): 257-264 (2010)
  • Suet-Peng Yong, Jeremiah D. Deng, Martin K. Purvis: Modelling semantic context for novelty detection in wildlife scenes. ICME 2010: 1254-1259
  • Brendon J. Woodford: Evolving neurocomputing systems for horticulture applications. Appl. Soft Comput. 8(1): 564-578 (2008)
  • J. D. Deng, C. Simmermacher and S. Cranefield. A study on feature analysis for musical instrument classification. IEEE Trans. System, Man and Cybernetics - Part B, 38:429-438, 2008.
  • D. Deng: Content-based image collection summarization and comparison using self-organizing maps. Pattern Recognition 40(2): 718-727 (2007)
  • Jeremiah D. Deng, Matthew T. Gleeson: Automatic Sapstain Detection in Processed Timber. Australian Conference on Artificial Intelligence 2007: 637-641
  • Brendon J. Woodford, Nikola K. Kasabov: Ensembles of EFuNNs: An Architecture for a Mutlimodule Classifier. FUZZ-IEEE 2001: 1573-1576
  • D. Deng, Nikola K. Kasabov: On-line pattern analysis by evolving self-organizing maps. Neurocomputing 51: 87-103 (2003)
  • D. Deng, Nikola K. Kasabov: An evolving localised learning model for on-line image colour quantisation. ICIP (1) 2001: 906-909
  • D. Deng, Nikola K. Kasabov: ESOM: An Algorithm to Evolve Self-Organizing Maps from On-Line Data Streams. IJCNN (6) 2000: 3-8