A Novel Gaze Processing Framework Using Crosscorrelation and Recurrence Quantification Analysis to Differentiate Expert Performances Veerabhadrappa, Rakesh, Hettiarachchi, I, Hanoun, Samer, Jia, D, Hosking, S and Bhatti, Asim 2020, A Novel Gaze Processing Framework Using Crosscorrelation and Recurrence Quantification Analysis to Differentiate Expert Performances, in DHSS 2020 : Proceedings of the 2020 Defence Human Sciences Symposium, Defence Science and Technology Group, [Melbourne, Vic.], pp. 1-2. Attached Files Name Description MIMEType Size Downloads Title A Novel Gaze Processing Framework Using Crosscorrelation and Recurrence Quantification Analysis to Differentiate Expert Performances Author(s) Veerabhadrappa, Rakesh Hettiarachchi, I orcid.org/0000-0002-8697-1515 Hanoun, Samer Jia, D Hosking, S orcid.org/0000-0001-6876-1437 Bhatti, Asim Conference name Defence Human Sciences. Symposium (2020 : Melbourne, Vic.) Conference location Melbourne, Vic. Conference dates 2020/12/07 - 2020/12/09 Title of proceedings DHSS 2020 : Proceedings of the 2020 Defence Human Sciences Symposium Publication date 2020 Start page 1 End page 2 Total pages 2 Publisher Defence Science and Technology Group Place of publication [Melbourne, Vic.] Language eng Field of Research 170205 Neurocognitive Patterns and Neural Networks 080109 Pattern Recognition and Data Mining 090303 Biomedical Instrumentation 090609 Signal Processing 080602 Computer-Human Interaction Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1 Full written paper - refereed Persistent URL http://hdl.handle.net/10536/DRO/DU:30151572 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment Institute for Intelligent Systems Research and Innovation (IISRI) Open Access Checking Related Links Link Description Connect to Elements publication management system Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Fri, 21 May 2021, 18:27:29 EST Sat, 22 May 2021, 05:01:59 EST Fri, 06 May 2022, 06:02:04 EST Tue, 10 May 2022, 12:10:17 EST Tue, 10 May 2022, 14:41:19 EST Tue, 10 May 2022, 16:25:41 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 13 Abstract Views, 5 File Downloads  -  Detailed Statistics Created: Fri, 21 May 2021, 18:27:29 EST