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Now showing items 1-13 of 13

  • Arbitrary Precision and Low Complexity Micro-Architectural Arithmetic Optimisations of Machine Learning Algorithms for Compute Bound and High-Performance Systems 

    Garland, James Philip (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2021)
    Artificial intelligence is becoming ubiquitous and pervasive in our daily lives. Machine learning (ML), a subset of Artificial intelligence (AI), supplies more accurate internet searches, voice recognition in home appliances, ...
  • Collaboration community formation in open systems for agents with multiple goals 

    GOLPAYEGANI, FATEMEH (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2018)
    Agents frequently coordinate their behaviour and collaborate to achieve a shared goal, share constrained resources, or accomplish a complex task that they cannot do alone. Forming an effective collaboration community in ...
  • Efficient GPU usage for rendering of Volume Data 

    GANTER, DAVID (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2020)
    Visualising medical images or scientific data that can be shown in 3D poses some interesting challenges. This thesis investigates two distinct areas of Direct Volume Rendering (DVR); time-varying datasets on emerging ...
  • Ego-hand Gesture Recognition in Trimmed and Untrimmed Videos for Interactions in Augmented and Virtual Reality. 

    Chalasani, Tejo Krishna (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2021)
    Hand gestures are used as a way of communication in our daily lives. Using hand gestures to interact with the virtual environment in Augmented and Virtual reality is a natural extension from the real to the virtual scenario. ...
  • Enhanced PON Architectures for Converged Access Networks for 5G and Beyond 

    Das, Sandip (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2022)
    In the past few years, the existing telecommunication networks are challenged to support the growing number of internet-reliant devices (such as smartphones and other smart devices), increasing penetration of mobile and ...
  • Improving Robustness Falsification for Medical Device Software 

    Quan, Wenji (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2021)
    The artificial Pancreas(AP) is a closed-loop system based on the combination of a continuous glucose monitor, a computer-controlled algorithm, and an insulin pump (Blauw et al., 2016). Insulin pumps are designed for ...
  • Modelling Light Field Visual Attention: A Saliency Field Approach 

    Gill, Ailbhe (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2022)
    Light field imaging is becoming more accessible, hence understanding how people perceive and interact with it will be of immense value. Although visual attention has been explored for traditional 2D images, we extend this ...
  • On Multi-Radio Multi-ServerPowered Multi-Access EdgeComputing 

    Ali, Asad (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2023)
    Highly intelligent, automated and ubiquitous digital world will be hallmark of the coming decade. To achieve this, we need high-speed, highly-reliable connectivity between physical, digital and biological world. In terms ...
  • Techno-economics of Optical Access Network Sharing 

    AFRAZ, NIMA (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2020)
    Several parallel trends, including the growing number of Internet reliant devices/services, increasing Internet penetration rates, and the continuing popularity of bandwidth-hungry multimedia content contribute to the ...
  • User Expertise Modelling Using Social Network Data 

    XU, YU (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2018)
    The ability to understand the expertise of online users is a key component for delivering effective information services such as talent seeking and user recommendation. However, users are often unwilling to make the effort ...
  • Using NLP Techniques to Enhance Content Discoverability and Reusability for Adaptive Systems 

    BAYOMI, MOSTAFA MOHAMED (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2019)
    The volume of digital content resources written as text documents is growing every day, at an unprecedented rate. Because this content is generally not structured as easy-to-handle units, it can be very difficult for users ...
  • Using NLP Techniques to Enhance Content Discoverability and Reusability for Adaptive Systems 

    BAYOMI, MOSTAFA (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2019)
    The volume of digital content resources written as text documents is growing every day, at an unprecedented rate. Because this content is generally not structured as easy-to-handle units, it can be very difficult for users ...