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  • Browsing Open Theses & Dissertations by Thesis Supervisor
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Browsing Open Theses & Dissertations by Thesis Supervisor "Kasabov, Nikola"

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Now showing items 1-20 of 41

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    • Adaptive Methods for Spatiotemporal Stream Data Mining 

      Hartono, Reggio Nurtanio (Auckland University of Technology, 2018)
      The availability of temporal and spatiotemporal data is increasing, and the use of traditional statistical techniques to deal with such data is insufficient. Novel methods that are capable of adapting to changing patterns ...
    • Affective Computing Using Brain-Inspired Spiking Neural Networks 

      Tan, Clarence (Auckland University of Technology, 2021)
      The interaction between humans and computational devices are becoming more and more common with the advent of personal digital devices, wearable systems, and other technological interventions. The field of affective computing ...
    • Age Invariant Face Recognition Via Aging Modelling 

      Alvi, Fahad Bashir (Auckland University of Technology, 2017)
      Aging is a complex problem because at different age points different changes occur in the human face. From childhood to teenage the changes are mostly related to craniofacial growth. At maturity the changes are mostly ...
    • An ontology driven knowledge discovery framework for Dynamic Domains: methodology, tools and a Biomedical case 

      Gottgtroy, Paulo (Auckland University of Technology, 2010)
      The explosive growth in the volume of data and the growing number of disparate data sources is bringing enormous opportunities and challenges to many research communities. In the biomedical domain, the challenge of knowledge ...
    • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data 

      Bahrami, Helena (Auckland University of Technology, 2021)
      Spiking neural networks (SNN) represent the third generation of the neural networks. They are inspired by the information processing principles in the human brain. The theory and applications of SNN can further benefit ...
    • A brain-computer interface based on a spiking neural network architecture – NeuCube and neuro-feedback 

      Bhattacharya, Wriju (Auckland University of Technology, 2015)
      In an average human brain, there are about 100 billion neurons connected by synapses that transmits electro-chemical signals to the different parts of the body. Brain Computer Interfacing (BCI) can be used to study and ...
    • Comparative Analysis of Traditional Machine Learning Methods and Spiking Neural Networks for Spatio-temporal Data Mining 

      Nayak, Parag Ganesh (Auckland University of Technology, 2016)
      A new framework in this study, which uses spiking neural networks for learning spectro-temporal and spatio-temporal data, is the NeuCube. The NeuCube is able to learn and classify and predict data, both in online and offline ...
    • Computational Modelling of Spatio-Temporal EEG Brain Data with Spiking Neural Networks 

      Capecci, Elisa (Auckland University of Technology, 2015)
      The research presented in this thesis is aimed at modelling, classification and understanding of functional changes in brain activity that forewarn of the onset and/or the progression of a neurodegenerative process that ...
    • Connectionist methods for data analysis and modelling of human motion in sporting activities 

      Bačić, Boris (Auckland University of Technology, 2012)
      This research concerns automation of qualitative analysis of human motion in sports, using a novel approach related to assessment and diagnostics, which is required to provide a general user with coaching experience in ...
    • CuWITH: a curiosity driven robot for office environmental security 

      Gordon, Sean William (Auckland University of Technology, 2009)
      The protection of assets is an important part of daily life. Currently this is done using a combination of passive security cameras and security officers actively patrolling the premises. However, security officers, being ...
    • Deep Learning and Knowledge Representation in Brain-Inspired Spiking Neural Networks for Brain-Computer Interfaces 

      Kumarasinghe, Kumara Vidanalage Dona Chithrangi Kaushalya (Auckland University of Technology, 2021)
      Brain-Computer Interfaces aim at decoding neural commands from neurological signals and translate them into machine commands for manipulating digital devices. It provides a way of bypassing affected neural pathways in ...
    • Detection of susceptibility to Multiple Sclerosis from Single Nucleotide Polymorphism data 

      Breen, Vivienne Ruth (Auckland University of Technology, 2013)
      For many diseases that are genetically based, the date of onset is not predetermined or even predictable. To aid in assisting diagnosis of these diseases it is important to understand the person’s susceptibility to developing ...
    • Development of a new computational model for mapping, learning and mining of 3D spatio-temporal fMRI data 

      Murli, Norhanifah (Auckland University of Technology, 2015)
      The application of data mining techniques, particularly classification of spatio-temporal 3D functional magnetic resonance images has received growing attention in the literature. Spatio or spatial component as well as ...
    • Development of Spiking Neural Network Methods for Spatio-temporal Brain Data Analysis 

      Doborjeh, Maryam (Auckland University of Technology, 2019)
      This thesis proposes methods employing an evolving Spiking Neural Network (SNN) architecture for the analysis of spatio-temporal neuroimaging data. Multivariate Spatio-Temporal Brain Data (STBD) is intrinsically complex ...
    • Evaluation and Improvement of Current Computational Tools for Metabolomics Data Analysis 

      Li, SiMing (Auckland University of Technology, 2017)
    • Evolving connectionist systems for adaptive decision support with application in ecological data modelling 

      Soltic, Snjezana (Auckland University of Technology, 2009)
      Ecological modelling problems have characteristics both featured in other modelling fields and specific ones, hence, methods developed and tested in other research areas may not be suitable for modelling ecological problems ...
    • Evolving probabilistic spiking neural networks for modelling and pattern recognition of spatio-temporal data on the case study of Electroencephalography (EEG) brain data 

      Nuntalid, Nuttapod (Auckland University of Technology, 2012)
      The use of Electroencephalography (EEG) in Brain Computer Interface (BCI) domain presents a challenging problem due to presence of spatial and temporal aspects inherent in the EEG data. Many studies either transform the ...
    • Evolving spiking neural networks for adaptive audiovisual pattern recognition 

      Wysoski, Simei Gomes (Auckland University of Technology, 2008)
      This dissertation presents new modular and integrative information methods and systems inspired by the way the brain performs information processing, in particular, pattern recognition. The proposed artificial systems use ...
    • Evolving Spiking Neural Networks for Spatio- and Spectro- Temporal Data Analysis: Models, Implementations, Applications 

      Scott, Nathan Matthew (Auckland University of Technology, 2015)
      Arguably the most significant challenge in modern machine learning regards how we address the complexities of Spatio- and Spectro-Temporal Data (SSTD); i.e., data with some spatial, spectral, and temporal component. ...
    • Feasibility analysis of using NeuCube 3D SNN environment for spatio-temporal EEG data classification related to perception of art 

      Turkova, Yulia (Auckland University of Technology, 2014)
      This thesis is a feasibility study of using a Spiking Neural Network (SNN) architecture named NeuCube for the classification of electroencephalography (EEG) data related to the perception of art. We have performed ...

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