Dr Adeline Paiement
Lecturer
Computer Science
Telephone: (01792) 604111
Room: Office - 961
First Floor
Talbot Building
Singleton Campus

Areas of Expertise

  • Computer vision
  • Machine learning
  • Astrophysics image analysis
  • AI-assisted healthcare
  • Medical image analysis

Publications

  1. & Manifold modeling of the beating heart motion. Medical Image Analysis and Understanding.
  2. & Evaluation of cupboard door sensors for improving activity recognition in the kitchen. Presented at PerHealth workshop, Athens, Greece: PerHealth2018 – Third IEEE PerCom Workshop on Pervasive Health Technologies.
  3. & Energy expenditure estimation using visual and inertial sensors. IET Computer Vision
  4. & (2014). Online quality assessment of human movement from skeleton data. Presented at BMVC 2014 - Proceedings of the British Machine Vision Conference 2014, doi:10.5244/C.28.79
  5. & (2015). Skeleton-Free Body Pose Estimation from Depth Images for Movement Analysis. Presented at Proceedings of the IEEE International Conference on Computer Vision, doi:10.1109/ICCVW.2015.49

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Teaching

  • CSCM35 Big Data and Data Mining

    This course is an introductory course on data mining and its role in science and engineering. Data mining refers to the computational process of discovering patterns in large data sets. The main goal of the course is for students to gain practical data mining experience. The module is aimed at students with previous experience in programming and statistics, and preferably basic knowledge of the Python language.

  • CSCM58 High Performance Computing in C/C++

    This course is an introductory course on high-performance computing (HPC) and its role in science and engineering. High-performance computing refers to a specialized use and programming of supercomputers, computer clusters, and related architectures and software to speed up computations. The main goal of the class is for students to gain practical HPC experience. The module is aimed at students with previous experience in programming in a high-level programming language and preferably basic knowledge of the C/C++ language.

  • CSCM78 High-Performance Computing in C/C++

    This course gives an introduction into programming in C/C++ and then focusses on high-performance computing (HPC) and its role in science and engineering. High-performance computing refers to a specialized use and programming of supercomputers, computer clusters, and related architectures and software to speed up computations. The main goal of the class is for students to gain practical experience in C/C++ and HPC.

Supervision

  • n.a. (current)

    Student name:
    MRes
    Other supervisor: Dr Xianghua Xie
  • Estimating Left Ventricle Displacement Due To Heartbeat Using Manifold Learning and Deep Learning (current)

    Student name:
    MRes
    Other supervisor: Dr Xianghua Xie
  • Large scale characterisation of galaxy morphology: a deep learning approach (current)

    Student name:
    PhD
    Other supervisor: Dr Xianghua Xie
  • Interactive Visualization of Molecular Dynamics Simulation Data (current)

    Student name:
    PhD
    Other supervisor: Dr Bob Laramee
  • Visual Analysis of Translation Data (current)

    Student name:
    PhD
    Other supervisor: Dr Bob Laramee
  • 4D reconstruction of solar active regions from multi-spectral images using deep learning (current)

    Student name:
    PhD
    Other supervisor: Dr Xianghua Xie
  • 'Deep Learning Methods for Texture Analysis in Medical Imaging' (awarded 2018)

    Student name:
    MSc
    Other supervisor: Dr Xianghua Xie