Improving eye-tracking data quality: A framework for reproducible evaluations of detection algorithms

Link:

https://doi.org/10.25592/uhhfdm.13720

Autor/in:

Christopher Lukas Gundler

Verlag/Körperschaft:

Universität Hamburg

Erscheinungsjahr:

2023

Medientyp:

Text

Beschreibung:

The individual error scores for different pupil detection algorithms as reported in the manuscript "Improving eye-tracking data quality: A framework for reproducible evaluations of detection algorithms"

Beziehungen:

DOI 10.25592/uhhfdm.13719

Lizenzen:

https://creativecommons.org/licenses/by/4.0/legalcode
info:eu-repo/semantics/openAccess

Quellsystem:

Forschungsdatenrepositorium des UKE

Interne Metadaten

Quelldatensatz: oai:fdr.uni-hamburg.de:13720