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heiDATA is an institutional repository for Open Research Data from Heidelberg University. It is managed by the Competence Centre for Research Data, a joint institution of the University Library and the Computing Centre. If you are interested in publishing your data here, please see our author instructions and get in touch with us.
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Oct 18, 2021 - Heidelberg University Language and Cognition Lab
Kokje, Eesha; Gerwien, Johannes; Stutterheim, Christiane von, 2021, "Macro-event recognition in healthy aging, Alzheimer's disease, and mild cognitive impairment [Data]", https://doi.org/10.11588/data/HBDRBY, heiDATA, V1, UNF:6:GCBciA3UU6l8DlEK+BoTlw== [fileUNF]
The data set contains the data associated with the study on "Macro-event recognition in healthy aging, Alzheimer's disease, and mild cognitive impairment". The files include the javascript codes for running the experiments, the data, and example stimuli.
MS Word - 576.1 KB - MD5: 857a90ad837ef63a267b3592bd8fd2d1
DataDocumentation
Tab-Delimited - 3.5 KB - MD5: 1afe86316c2586cbdec02b8c6987d2ee
Data
Tab-Delimited - 1.7 KB - MD5: 0fc34dbbc3febf224c7a33840a25c984
Data
ZIP Archive - 7.6 KB - MD5: 2d9ea14142417fef1799d2844727804e
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Plain Text - 2.0 KB - MD5: 832bd694da5d8d52c98b0384244915c9
Documentation
Oct 12, 2021 - GIScience / Geoinformatics Research Group
Li, Hao; Zech, Johannes; Ludwig, Christina; Fendrich, Sascha; Shapiro, Aurelie; Schultz, Michael; Zipf, Alexander, 2021, "Automatic mapping of national surface water with OpenStreetMap and Sentinel-2 MSI data using deep learning [Research Data]", https://doi.org/10.11588/data/AAKAF9, heiDATA, V1
Large-scale mapping activities can benefit from the vastly increasing availability of earth observation (EO) data, especially when combined with volunteered geographical information (VGI) using machine learning (ML). High-resolution maps of inland surface water bodies are importa...
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