Probabilistic neuroscale for uncertainty visualisation

Mingmanas Sivaraksa; David Lowe

doi:10.1109/IV.2009.106

Probabilistic neuroscale for uncertainty visualisation

Mingmanas Sivaraksa^*, David Lowe

^*Corresponding author for this work

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

This paper is a study of low dimensional visualisation methods for data visualisation under uncertainty of the input data. It focuses on NeuroScale, the feed-forward neural networks algorithm by trying to make the algorithm ableto accommodate the uncertainty. The standard model is shown not to work well under high levels of noise within the data and need to be modified. The modifications of the model are verified by using synthetic data to show their ability to accommodate the noise.

Original language	English
Title of host publication	Information visualization
Pages	74-79
Number of pages	6
DOIs	https://doi.org/10.1109/IV.2009.106
Publication status	Published - 2009
Event	13th International Conference Information Visualisation, 2009 - Barcelona, Spain Duration: 15 Jul 2009 → 17 Jul 2009

Publication series

Name	IEEE Conference Publications
Publisher	IEEE
ISSN (Print)	1550-6037

Conference

Conference	13th International Conference Information Visualisation, 2009
Abbreviated title	IV 2009
Country/Territory	Spain
City	Barcelona
Period	15/07/09 → 17/07/09

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10.1109/IV.2009.106

Cite this

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title = "Probabilistic neuroscale for uncertainty visualisation",

abstract = "This paper is a study of low dimensional visualisation methods for data visualisation under uncertainty of the input data. It focuses on NeuroScale, the feed-forward neural networks algorithm by trying to make the algorithm ableto accommodate the uncertainty. The standard model is shown not to work well under high levels of noise within the data and need to be modified. The modifications of the model are verified by using synthetic data to show their ability to accommodate the noise.",

author = "Mingmanas Sivaraksa and David Lowe",

year = "2009",

doi = "10.1109/IV.2009.106",

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isbn = "978-0-7695-3733-7",

series = "IEEE Conference Publications",

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AB - This paper is a study of low dimensional visualisation methods for data visualisation under uncertainty of the input data. It focuses on NeuroScale, the feed-forward neural networks algorithm by trying to make the algorithm ableto accommodate the uncertainty. The standard model is shown not to work well under high levels of noise within the data and need to be modified. The modifications of the model are verified by using synthetic data to show their ability to accommodate the noise.

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U2 - 10.1109/IV.2009.106

DO - 10.1109/IV.2009.106

M3 - Conference publication

AN - SCOPUS:70449485823

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T2 - 13th International Conference Information Visualisation, 2009

Y2 - 15 July 2009 through 17 July 2009

ER -

Probabilistic neuroscale for uncertainty visualisation

Abstract

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