DeltaNN: Assessing the Impact of Computational Environment Parameters on the Performance of Image Recognition Models

Louloudakis, N., Gibson, P. , Cano Reyes, J. and Rajan, A. (2023) DeltaNN: Assessing the Impact of Computational Environment Parameters on the Performance of Image Recognition Models. In: 39th IEEE International Conference on Software Maintenance and Evolution (ICSME 2023), Bogota, Columbia, 1-6 Oct 2023, (Accepted for Publication)

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Item Type:Conference Proceedings
Additional Information:Authors, Ajitha Rajan and Nikolaos Louloudakis, would like to acknowl- edge the support received from funding sources, UKRI Trustworthy Au- tonomous Systems Node in Governance and Regulation (EP/V026607/1) and Royal Society Industry Fellowship, for this work.
Status:Accepted for Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Cano Reyes, Dr Jose and Gibson, Mr Perry
Authors: Louloudakis, N., Gibson, P., Cano Reyes, J., and Rajan, A.
College/School:College of Science and Engineering > School of Computing Science
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
311600UKRI Trustworthy Autonomous Systems Node in Governance and RegulationAlice MillerEngineering and Physical Sciences Research Council (EPSRC)9790741 (EP/V026607/1)Computing Science