Studying Transfer of Learning using a Brain-Inspired Spiking Neural Network in the Context of Learning a New Programming Language [PDF]
, 2021 Transfer of learning (TL) has been an important research area for scholars, educators, and cognitive psychologists for over a century. However, it is not yet understood why applying existing knowledge and skills in a new context does not always follow ...
Fard, Mojgan +3 more
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Transfer Learning of Fuzzy Spatio-Temporal Rules in the NeuCube Brain-Inspired Spiking Neural Network: A Case Study on EEG Spatio-temporal Data:A Case Study on Spatio-Temporal Brain Data [PDF]
, 2023 The article demonstrates for the first time that a brain-inspired spiking neural network (SNN) architecture can be used not only to learn spatio-temporal data, but also to extract fuzzy spatio-temporal rules from such data and to update these rules ...
Doborjeh, Maryam +6 more
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Evolving Connectionist Systems for Adaptive Learning and Knowledge Discovery: Trends and Directions [PDF]
, 2015 This paper follows the 25 years of development of methods and systems for knowledge-based neural network systems and more specifically the recent evolving connectionist systems (ECOS).
Kasabov, N
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Towards the Holodeck: fully immersive virtual reality visualisation of scientific and engineering data [PDF]
, 2014 In this paper, we describe the development and operating principles of an immersive virtual reality (VR) visualisation environment that is designed around the use of consumer VR headsets in an existing wide area motion capture suite.
Connor, AM, Estevez, JE, Marks, S
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Emotion Recognition and Understanding Using EEG Data in A Brain-Inspired Spiking Neural Network Architecture [PDF]
, 2021 This paper is in the scope of emotion recognition by employing a brain-inspired recurrent spiking neural network (BI-SNN) architecture for modelling, mapping, learning, classifying, visualising, and understanding of spatio-temporal Electroencephalogram ...
Alzhrani, Wael +3 more
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Evolving spiking neural network model for PM2.5 hourly concentration prediction based on seasonal differences: A case study on data from Beijing and Shanghai [PDF]
, 2021 In recent years, the dangers that air pollutants pose to human health and the environment have received widespread attention. Although accurately predicting the air quality is essential to managing pollution and developing control policies, traditional ...
Kasabov, Nikola +3 more
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A Graph-Based Semi-Supervised k Nearest-Neighbor Method for Nonlinear Manifold Distributed Data Classification [PDF]
, 2016 $k$ Nearest Neighbors ($k$NN) is one of the most widely used supervised learning algorithms to classify Gaussian distributed data, but it does not achieve good results when it is applied to nonlinear manifold distributed data, especially when a very ...
Kasabov, Nikola +4 more
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Network-based method for inferring cancer progression at the pathway level from cross-sectional mutation data [PDF]
, 2016 Large-scale cancer genomics projects are providing a wealth of somatic mutation data from a large number of cancer patients. However, it is difficult to obtain several samples with a temporal order from one patient in evaluating the cancer progression ...
Gao, L, Kasabov, N, Wu, H
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Navigation Learning Assessment Using EEG-Based Multi-Time Scale Spatiotemporal Compound Model
IEEE Transactions on Neural Systems and Rehabilitation EngineeringThis study presents a novel method to assess the learning effectiveness using Electroencephalography (EEG)-based deep learning model. It is difficult to assess the learning effectiveness of professional courses in cultivating students’ ability ...
Lingling Wang +6 more
doaj +1 more source
Modeling functional brain connections in methamphetamine and opioid abusers
Medicine in Novel Technology and DevicesSubstance abuse has become a significant problem worldwide. The primary purpose of this study was to model the functional brain connectivity in methamphetamines (Meth) and opioids (Op) groups in comparison with the healthy control (HC) group.
Nasimeh Marvi +2 more
doaj +1 more source