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  DCF: An Efficient and Robust Density-Based Clustering Method 

  Zhang, Mimi; Tobin, Joshua (2021)

  Density-based clustering methods have been shown to achieve promising results in modern data mining applications. A recent approach, Density Peaks Clustering (DPC), detects modes as points with high density and large ...
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  Semantic image segmentation based on spatial relationships and inexact graph matching 

  Dahyot, Rozenn (2020)

  We propose a method for semantic image segmentation, combining a deep neural network and spatial relationships between image regions, encoded in a graph representation of the scene. Our proposal is based on inexact graph ...
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  An Integrated Framework for Estimating the Number of Classes with Application for Species Estimation 

  Al-Ghamdi, Asmaa (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2021)

  The two most common approaches for estimating the number of distinct classes within a population are either to use sampling data directly with combinatorial arguments or to extrapolate historical discovery data. However, ...
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  Image Restoration Using Deep Learning 

  ALBLUWI, FATMA HAMED (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)

  In this thesis, we propose several convolutional neural network (CNN) architectures with fewer parameters compared to state-of-the-art deep structures to restore original images from degraded versions. Employing fewer ...
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  A Heuristic Policy for Maintaining Multiple Multi-State Systems 

  Zhang, Mimi (2020)

  This work is concerned with the optimal allocation of limited maintenance resources among a collection of competing multi-state systems, and the dynamic of each multi-state system is modelled by a Markov chain. Determining ...

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