Browsing by Author "Price, Christopher"

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  • Snooke, Neal; Price, Christopher (2011-12-12)
    This paper builds on the ability to produce a comprehensive automated set of component fault¿ observation relations for vehicle on-board systems using qualitative model based reasoning techniques. Observations are typically ...
  • Snooke, Neal; Price, Christopher (2011-12-12)
    This paper builds on the ability to produce a comprehensive automated set of component fault– observation relations for vehicle on-board systems using qualitative model based reasoning techniques. Observations are typically ...
  • Song, Jingping; Zhu, Zhiliang; Price, Christopher (2014)
    Intrusion detection is an important task for network operators in today’s Internet. Traditional network intrusion detection systems rely on either specialized signatures of previously seen attacks, or on labeled traffic ...
  • Song, Jingping; Zhu, Zhiliang; Scully, Peter Matthew David; Price, Christopher (2014-07)
    As network-based technologies become omnipresent, intrusion detection and prevention for these systems become increasingly important. This paper proposed a modified mutual information-based feature selection algorithm ...
  • Bai, Bendu; Li, Ying; Fan, Jiulun; Price, Christopher; Shen, Qiang (2015-04-01)
    In this paper, we propose a novel object tracking method that can work well in challenging scenarios such as appearance changes, motion blurs, and especially partial occlusions and noise. Our method applies bilateral ...
  • Li, Ying; Li, Fangyi; Yang, Kaixing; Price, Christopher; Shen, Qiang (2017-08-16)
    This study deals with an important issue that is often encountered with the registration of remote sensing images which are obtained at different times and/or through inter/intra sensors. Remote sensing images may differ ...
  • Chen, Chengyuan; MacParthalain, Neil; Li, Ying; Price, Christopher; Quek, Chai; Shen, Qiang (2016-07-10)
    Fuzzy rule interpolation forms an important approach for performing inference with systems comprising sparse rule bases. Even when a given observation has no overlap with the antecedent values of any existing rules, fuzzy ...
  • Song, Jingping; Zhu, Zhiliang; Scully, Peter Matthew David; Price, Christopher (Springer Nature, 2013-11-11)
    In this work, a new method for classification is proposed consisting of a combination of feature selection, normalization, fuzzy C means clustering algorithm and C4.5 decision tree algorithm. The aim of this method is to ...