• Adaptive background modeling for land and water composition scenes 

      Zhao, Jing; Pang, Shaoning; Hartill, Bruce; Sarrafzadeh, Hossein (International Conference on Image Analysis and Processing (ICIAP), 2015-09)
      In the context of maritime boat ramps surveillance, this paper proposes an Adaptive Background Modeling method for Land and Water composition scenes (ABM-lw) to interpret the traffic of boats passing across boat ramps. We ...
    • Analysis and configuration of boundary difference calculations 

      Dacey, Simon; Pang, Shaoning; Song, Lei; Zhu, Lei (ICONIP, 2014-11)
      In the field of land management, stakeholders (people) everywhere have many disputes over the location of boundaries between private land and public land. We find that the stakeholders disagree with each other over boundaries. ...
    • Dynamic class imbalance learning for incremental LPSVM 

      Pang, Shaoning; Zhu, Lei; Chen, Gang; Sarrafzadeh, Hossein; Ban, Tao; Inoue, Daisuke (Neural Networks, 2013-02)
      Linear Proximal Support Vector Machines (LPSVMs), like decision trees, classic SVM, etc. are originally not equipped to handle drifting data streams that exhibit high and varying degrees of class imbalance. For online ...
    • The global cyber security workforce : an ongoing human capital crisis 

      Fourie, Leon; Pang, Shaoning; Kingston, Tamsin; Hettema, Hinne; Watters, Paul; Sarrafzadeh, Hossein (Global Business and Technology Association, 2014-07)
      Cyber threats pose substantial risk to government, businesses and individuals. There is an alarming shortage of trained professionals and academic programs to train and produce these professionals. Many countries including ...
    • Incremental and decremental max-flow for online semi-supervised learning 

      Zhu, Lei; Pang, Shaoning; Sarrafzadeh, Hossein; Ban, Tao; Inoue, Daisuke (Institute of Electrical and Electronics Engineers (IEEE), 2016-04-13)
      Max-flow has been adopted for semi-supervised data modelling, yet existing algorithms were derived only for the learning from static data. This paper proposes an online max-flow algorithm for the semi-supervised learning ...
    • An Intelligent Agent Based Land Encroachment Detection Approach 

      Dacey, Simon; Song, Lei; Pang, Shaoning (Asia Pacific Neural Network Assembly (APNNA), 2013)
      Land management and planning is essential to assist the economic growth, sustainable resource use and environmental protection of a city. This paper describes a novel approach to automatic encroachment detection to assist ...
    • Machine learning technology and its application to computer games for health education 

      Chen, Aaron; Baghaei, Nilufar; Sarrafzadeh, Hossein; Pang, Paul; Tsoulis, Athina; Court, Gudrun (2012)
      Driven by an initiative of the Adult & Paediatric Diabetes Psychology Service of New Zealand, research has been performed to develop new mechanisms, in the form of computer games, to educate children and teenagers about ...
    • Modelling land water composition scene for maritime traffic surveillance 

      Pang, Shaoning; Zhao, Jing.; Hartill, B.; Sarrafzadeh, Hossein (Inderscience Enterprises, 2016)
      Background modelling, used in many vision systems, must be robust to environmental change, yet sensitive enough to identify all moving objects of interest. Existing background modelling approaches have been developed to ...
    • Service provision control in federated service providing systems 

      Chen, Gang; Sarrafzadeh, Hossein; Pang, Shaoning (2013-03)
      Different from traditional P2P systems, individuals nodes of a Federated Service Providing (FSP) system play a more active role by offering a variety of domain-specific services. The service provision control (SPC) problem ...
    • Smart Task Orderings for Active Online Multitask Learning 

      Pang, Paul; An, Jianbei; Zhao, Jing; Li, Xiaosong; Ban, Tao; Inoue, Daisuke; Sarrafzadeh, Hossein (Society for Industrial and Applied Mathematics, Activity Group on Data Mining and Analytics, 2014-04-26)
      This paper promotes active oMTL (i.e., Online Multitask Learning with task selection) by proposing two smart task ordering approaches: QR-decomposition Ordering and Minimal-loss Ordering, in which the optimal sequence of ...