Now showing items 1-5 of 36

  • A 3-factor epistatic model predicts digital ulcers in Italian scleroderma patients

    Beretta, Lorenzo; Santaniello, Alessandro; Mayo, Michael; Cappiello, Francesca; Marchini, Maurizio; Scorza, Raffaella (Elsevier, 2010)
    Background The genetic background may predispose systemic sclerosis (SSc) patients to the development of digital ulcers (DUs). Methods Twenty-two functional cytokine single nucleotide polymorphisms (SNPs) and 3 HLA class ...
  • 3D face recognition using multiview keypoint matching

    Mayo, Michael; Zhang, Edmond Yiwen (IEEE, 2009)
    A novel algorithm for 3D face recognition based point cloud rotations, multiple projections, and voted keypoint matching is proposed and evaluated. The basic idea is to rotate each 3D point cloud representing an individual’s ...
  • Adaptive feature thresholding for off-line signature verification

    Larkins, Robert L.; Mayo, Michael (2008)
    This paper introduces Adaptive Feature Thresholding (AFT) which is a novel method of person-dependent off-line signature verification. AFT enhances how a simple image feature of a signature is converted to a binary feature ...
  • An Adaptive Model-based Mutation Operator for the Wind Farm Layout Optimisation Problem

    Mayo, Michael; Daoud, Maisa (IEEE, 2015)
    A novel mutation operator for the wind farm layout optimisation problem is proposed and tested. When a wind farm layout is simulated, statistics such as an individual turbine’s wake free ratio can be computed. These ...
  • Alternating model trees

    Frank, Eibe; Mayo, Michael; Kramer, Stefan (ACM Press, 2015)
    Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes. In this paper, we propose ...

Showing up to 5 theses - most recently added to Research Commons first.

  • Linear Genetic Programming with Experience

    Liu, Liang (University of Waikato, 2015)
    A novel method of using Machine Learning (ML) algorithms to improve the performance of Linear Genetic Programming (LGP) is studied. In this study, structures used to organize the trained ML models are called Experience ...
  • Meta-Learning and the Full Model Selection Problem

    Sun, Quan (University of Waikato, 2014)
    When working as a data analyst, one of my daily tasks is to select appropriate tools from a set of existing data analysis techniques in my toolbox, including data preprocessing, outlier detection, feature selection, learning ...
  • Improving the Evaluation of Network Anomaly Detection Using a Data Fusion Approach

    Löf, Andreas (University of Waikato, 2013)
    Currently, the evaluation of network anomaly detection methods is often not repeatable. It is difficult to ascertain if different implementations of the same methods have the same performance or the relative performance ...
  • Improving Bags-of-Words model for object categorization

    Zhang, Edmond Yiwen (University of Waikato, 2013)
    In the past decade, Bags-of-Words (BOW) models have become popular for the task of object recognition, owing to their good performance and simplicity. Some of the most effective recent methods for computer-based object ...
  • Sequence-based protein classification: binary Profile Hidden Markov Models and propositionalisation

    Mutter, Stefan (University of Waikato, 2011)
    Detecting similarity in biological sequences is a key element to understanding the mechanisms of life. Researchers infer potential structural, functional or evolutionary relationships from similarity. However, the concept ...