Group headed by Andreas Bulling of the Human-Computer Interaction and Cognitive Systems department of the University of Stuttgart.
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561 to 570 of 1,097 Results
participant_3.0.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 245.1 KB - MD5: 24b0910d68c5bef997e524438a9800a9
participant_3.1.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 912.0 KB - MD5: 124ba4448c2ae77649338f21fff663b8
participant_3.2.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 835.8 KB - MD5: 11bab2d095e46ce337dfdefc689c9a9a
participant_3.3.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 741.1 KB - MD5: 0ef127ac15b5b05a2b355a6b92848980
participant_4.0.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 172.0 KB - MD5: 9a0d3c6e6fea801818ee18f0b731f81d
participant_4.1.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 766.1 KB - MD5: ffc2e958e1e8eeb42e5aee694f0d5f6e
participant_4.2.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 677.3 KB - MD5: ad7f1f1b4288a66632650448eb61e05e
participant_4.3.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 940.6 KB - MD5: a5c7000add530ab36f7e90adc57e262e
participant_4.4.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 270.1 KB - MD5: 5d57c12b181bb82ffe76681c33357a17
participant_5.0.mat
Oct 20, 2022 - Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"
MATLAB Data - 241.7 KB - MD5: c276ecdee87882dea1381f2b4ef4d798
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