The University of Southampton
University of Southampton Institutional Repository

A modelled classification approach to the automatic analysis of hand drawn neuropsychological tests

A modelled classification approach to the automatic analysis of hand drawn neuropsychological tests
A modelled classification approach to the automatic analysis of hand drawn neuropsychological tests
Stasiak, Arkadiusz
0b2f3faf-4535-45f5-8bc2-9c43aa956075
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Fairhurst, Michael
6a82d154-93fe-4657-bcee-934d5c888192
Stasiak, Arkadiusz
0b2f3faf-4535-45f5-8bc2-9c43aa956075
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Fairhurst, Michael
6a82d154-93fe-4657-bcee-934d5c888192

Stasiak, Arkadiusz, Guest, Richard and Fairhurst, Michael (2008) A modelled classification approach to the automatic analysis of hand drawn neuropsychological tests. ICFHR 2008: 11th International Conference on Frontiers in Handwriting Recognition, , Montreal, Canada. 19 - 21 Aug 2008.

Record type: Conference or Workshop Item (Paper)

This record has no associated files available for download.

More information

Published date: August 2008
Venue - Dates: ICFHR 2008: 11th International Conference on Frontiers in Handwriting Recognition, , Montreal, Canada, 2008-08-19 - 2008-08-21

Identifiers

Local EPrints ID: 489583
URI: http://eprints.soton.ac.uk/id/eprint/489583
PURE UUID: bccf57ce-e4f4-4c87-b70d-c56098dfa1eb
ORCID for Richard Guest: ORCID iD orcid.org/0000-0001-7535-7336

Catalogue record

Date deposited: 29 Apr 2024 16:35
Last modified: 30 Apr 2024 02:05

Export record

Contributors

Author: Arkadiusz Stasiak
Author: Richard Guest ORCID iD
Author: Michael Fairhurst

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×