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ZIP Archive - 79.8 GB - MD5: 95c8dea34cab50daff44ace6de15ae4c
ZIP Archive - 73.3 GB - MD5: 92daec063dd7350913eca5f17c7406ac
ZIP Archive - 71.4 GB - MD5: 9225984e5e671c3d2208bfba359994b7
Nov 19, 2025 - University of Agder
Muhammad Hamza Zafar, 2025, "E-GMDCSA24: Event Based Human Fall Detection Dataset", https://doi.org/10.18710/T0GJXA, DataverseNO, V2
This dataset consists of RGB-to-Event converted data for Human Fall Detection. It is intended for use in Human Fall Detection tasks leveraging Neuromorphic/Event-based Vision. The dataset includes Event images, RGB images, and files containing raw event data.
Plain Text - 3.6 KB - MD5: 071859fcbea9f9fef5827f282df7869c
This README file gives detailed information about the Dataset Directories and the methods used for generation of this dataset.
Nov 19, 2025 - University of Agder
Muhammad Hamza Zafar, 2025, "E-CAUCAFall: Event Based Human Fall Detection Dataset", https://doi.org/10.18710/ITNCWP, DataverseNO, V1
This dataset consists of RGB-to-Event converted data for Human Fall Detection. It is intended for use in Human Fall Detection tasks leveraging Neuromorphic/Event-based Vision. The dataset includes Event images, RGB images, and files containing raw event data.
Plain Text - 3.7 KB - MD5: 87a93b8491a625d88b5d9658dda4f3ab
This README file gives detailed information about the Dataset Directories and the methods used for generation of this dataset.
ZIP Archive - 9.8 GB - MD5: 46291f7357b1f6d76db514582e4e90d7
Zip file contains the dataset which is described in the README file.
ZIP Archive - 32.4 GB - MD5: a153401abe73d40388a6eb82617e3909
Zip file contains the dataset which is described in the README file.
Nov 19, 2025 - TROLLing
Vander Haegen, Flor, 2025, "German universal concessive conditionals with wh-clause-initial and wh-clause-medial marking", https://doi.org/10.18710/FVA2YV, DataverseNO, V1
These are the data analysed in Chapter 6 of Vander Haegen's dissertation entitled "Konstruktionsgrammatik und Variation. Eine Mikrotypologie universaler Irrelevanzgefüge im Gegenwartsdeutschen". The dataset includes an annotated sample of N = 3000 German written universal concessive conditionals (e.g. "Was immer auch passiert, ich bin für dich da!"...
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