Immersive Visualisation of 3-dimensional Spiking Neural Networks

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aut.relation.endpage9
aut.relation.journalEvolving Systemsen_NZ
aut.relation.startpage1
aut.researcherMarks, Stefan
dc.contributor.authorMarks, Sen_NZ
dc.date.accessioned2017-08-18T04:10:33Z
dc.date.available2017-08-18T04:10:33Z
dc.date.copyright2016-11-17en_NZ
dc.date.issued2016-11-17en_NZ
dc.description.abstractRecent development in artificial neural networks has led to an increase in performance, but also in complexity and size. This poses a significant challenge for the exploration and analysis of the spatial structure and temporal behaviour of such networks. Several projects for the 3D visualisation of neural networks exist, but they focus largely on the exploration of the spatial structure alone, and are using standard 2D screens as output and mouse and keyboard as input devices. In this article, we present NeuVis, a framework for an intuitive and immersive 3D visualisation of spiking neural networks in virtual reality, allowing for a larger variety of input and output devices. We apply NeuVis to NeuCube, a 3-dimensional spiking neural network learning framework, significantly improving the user’s abilities to explore, analyse, and also debug the network. Finally, we discuss further venues of development and alternative render methods that are currently under development and will increase the visual accuracy and realism of the visualisation, as well as further extending its analysis and exploration capabilities.en_NZ
dc.identifier.citationEvolving Systems, 1-9.
dc.identifier.doi10.1007/s12530-016-9170-8en_NZ
dc.identifier.issn1868-6486en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/10746
dc.publisherSpringeren_NZ
dc.relation.urihttp://link.springer.com/article/10.1007/s12530-016-9170-8en_NZ
dc.rightsAn author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at www.springerlink.com”. (Please also see Publisher’s Version and Citation).
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectSpiking neural network; 3-Dimensional; Visualisation; Virtual reality; Immersive
dc.titleImmersive Visualisation of 3-dimensional Spiking Neural Networksen_NZ
dc.typeJournal Article
pubs.elements-id214909
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/CoLab
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