Collaborative Artificial Intelligence

Group headed by Andreas Bulling of the Human-Computer Interaction and Cognitive Systems department of the University of Stuttgart.

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491 to 500 of 1,117 Results

P09_Annotation.npy Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models" Unknown - 238.7 MB - MD5: 247c26812a31a04f0f916df49e00e73e
P09_Recording.npy Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models" Unknown - 47.0 MB - MD5: bcd2633ce04eae28aa483a6cc20fc5d9
P09_Recording.tab Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models" Tabular Data - 58.2 MB - 9 Variables, 684865 Observations - UNF:6:ZK3P1/2Q6rfgKaBXvJ7Dvg==
P10_Annotation.npy Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models" Unknown - 350.8 MB - MD5: 393bcfdc1c1685d3799e53de2bdf76f1
P10_Annotation.tab Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models" Tabular Data - 61.4 MB - 1 Variables, 821033 Observations - UNF:6:e+zBXrUqyiKhK8j+WggZog==
P10_Recording.npy Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models" Unknown - 28.4 MB - MD5: 8b9e42574cf21c43b1fadbae79241222
P10_Recording.tab Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models" Tabular Data - 35.1 MB - 9 Variables, 414316 Observations - UNF:6:8GFYJtitgJZ5SNL4QdudXA==
Readme.txt Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models" Plain Text - 6.2 KB - MD5: fbdcd0543456fe29cf92925b012e4163
MPIIDPEye: Privacy-Aware Eye Tracking Using Differential Privacy Oct 28, 2022 Bulling, Andreas, 2022, "MPIIDPEye: Privacy-Aware Eye Tracking Using Differential Privacy", https://doi.org/10.18419/DARUS-3235, DaRUS, V1, UNF:6:1+E3rPNFm33/BHVCDizlJA== [fileUNF] We designed a privacy-aware VR interface that uses differential privacy, which we evaluate on a new 20-participant dataset for two privacy sensitive tasks. The data consists of eye gaze as participants read different types of documents. The dataset consists of a .zip file with two folders (Eye_Tracking_Data and Eye_Movement_Features), a .csv file w...
changelog.txt Oct 28, 2022 - MPIIDPEye: Privacy-Aware Eye Tracking Using Differential Privacy Plain Text - 160 B - MD5: 834846f181fed1e3d7c256bb7e9a5dd3

P09_Annotation.npy

Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models"

Unknown - 238.7 MB -

P09_Recording.npy

Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models"

Unknown - 47.0 MB -

P09_Recording.tab

Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models"

Tabular Data - 58.2 MB - 9 Variables, 684865 Observations -

P10_Annotation.npy

Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models"

Unknown - 350.8 MB -

P10_Annotation.tab

Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models"

Tabular Data - 61.4 MB - 1 Variables, 821033 Observations -

P10_Recording.npy

Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models"

Unknown - 28.4 MB -

P10_Recording.tab

Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models"

Tabular Data - 35.1 MB - 9 Variables, 414316 Observations -

Readme.txt

Oct 28, 2022 - Data for "Discovery of Everyday Human Activities From Long-term Visual Behaviour Using Topic Models"

Plain Text - 6.2 KB -

MPIIDPEye: Privacy-Aware Eye Tracking Using Differential Privacy

Oct 28, 2022

Bulling, Andreas, 2022, "MPIIDPEye: Privacy-Aware Eye Tracking Using Differential Privacy", https://doi.org/10.18419/DARUS-3235, DaRUS, V1, UNF:6:1+E3rPNFm33/BHVCDizlJA== [fileUNF]

We designed a privacy-aware VR interface that uses differential privacy, which we evaluate on a new 20-participant dataset for two privacy sensitive tasks. The data consists of eye gaze as participants read different types of documents. The dataset consists of a .zip file with two folders (Eye_Tracking_Data and Eye_Movement_Features), a .csv file w...

changelog.txt

Oct 28, 2022 - MPIIDPEye: Privacy-Aware Eye Tracking Using Differential Privacy

Plain Text - 160 B -

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