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Found 22 result(s)
The CMU Multi-Modal Activity Database (CMU-MMAC) database contains multimodal measures of the human activity of subjects performing the tasks involved in cooking and food preparation. The CMU-MMAC database was collected in Carnegie Mellon's Motion Capture Lab. A kitchen was built and to date twenty-five subjects have been recorded cooking five different recipes: brownies, pizza, sandwich, salad, and scrambled eggs.
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GTS AI is an Artificial Intelligence Company that offers excellent services to its clients. We use high definition images and use high quality data to analyze and help in Machine Learning Company . We are a dataset provider and we collect data in regards to artificial intelligence.
Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.
The CONP portal is a web interface for the Canadian Open Neuroscience Platform (CONP) to facilitate open science in the neuroscience community. CONP simplifies global researcher access and sharing of datasets and tools. The portal internalizes the cycle of a typical research project: starting with data acquisition, followed by processing using already existing/published tools, and ultimately publication of the obtained results including a link to the original dataset. From more information on CONP, please visit https://conp.ca
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The TRR170-DB was set up to manage data products of the collaborative research center TRR 170 'Late Accretion onto Terrestrial Planets' (https://www.trr170-lateaccretion.de/). However, meanwhile the repository also stores data by other institutions and researchers. Data include laboratory and other instrumental data on planetary samples, remote sensing data, geological maps and model simulations.
The UA Campus Repository is an institutional repository that facilitates access to the research, creative works, publications and teaching materials of the University by collecting, sharing and archiving content selected and deposited by faculty, researchers, staff and affiliated contributors.
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sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
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This data archive of experiments studying the dynamics of pedestrians is build up by the Institute for Advanced Simulation 7: Civil Safety Research of Forschungszentrum Jülich. The landing page provides our own data of experiments. Data of research colleagues are listed within the data archive at https://ped.fz-juelich.de/extda For most of the experiments, the video recordings, as well as the resulting trajectories of single pedestrians, are available. The experiments were performed under laboratory conditions to focus on the influence of a single variable. You are very welcome to use our data for further research, as long as you name the source of the data. If you have further questions feel free to contact Maik Boltes.
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Repository "Open Science Resource Atlas 2.0" aims to increase the accessibility, improve the quality and extend the reusability of science resources. Repository focuses on the digital sharing of resources of great importance to the field of science and economy. These include publications, scripts, lectures, 3D models, audio and video recordings, photos, input and output files of various computer programs, databases collecting data from various fields, machines, systems, language corpora and many others. The target group, apart from academics, students and doctoral students, is everyone interested, including entrepreneurs and, what is important and unique - disabled, blind, visually impaired and deaf people.
The Energy Data eXchange (EDX) is an online collection of capabilities and resources that advance research and customize energy-related needs. EDX is developed and maintained by NETL-RIC researchers and technical computing teams to support private collaboration for ongoing research efforts, and tech transfer of finalized DOE NETL research products. EDX supports NETL-affiliated research by: Coordinating historical and current data and information from a wide variety of sources to facilitate access to research that crosscuts multiple NETL projects/programs; Providing external access to technical products and data published by NETL-affiliated research teams; Collaborating with a variety of organizations and institutions in a secure environment through EDX’s ;Collaborative Workspaces
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The INESC TEC data repository showcases datasets produced or used by INESC TEC researchers and their partners. The repository is organized in four groups (institutional clusters). Computer Science, Power and Energy, Network and Intelligent Systems and Power and Energy.
This is the KONECT project, a project in the area of network science with the goal to collect network datasets, analyse them, and make available all analyses online. KONECT stands for Koblenz Network Collection, as the project has roots at the University of Koblenz–Landau in Germany. All source code is made available as Free Software, and includes a network analysis toolbox for GNU Octave, a network extraction library, as well as code to generate these web pages, including all statistics and plots. KONECT contains over a hundred network datasets of various types, including directed, undirected, bipartite, weighted, unweighted, signed and rating networks. The networks of KONECT are collected from many diverse areas such as social networks, hyperlink networks, authorship networks, physical networks, interaction networks and communication networks. The KONECT project has developed network analysis tools which are used to compute network statistics, to draw plots and to implement various link prediction algorithms. The result of these analyses are presented on these pages. Whenever we are allowed to do so, we provide a download of the networks.