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4,325
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Dataset results
4,325 results for “real”
A real-world energy management data set from a smart company building for optimization and machine learning
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Testing hormonal responses to real and simulated social challenges in a competitive female bird
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Improving real-time ultrasound spine imaging with a large-aperture array
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Real-time VIM thalamus recordings during peripheral nerve stimulation treatment for essential tremor: DBS intraoperative dataset
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Data from: A real data-driven simulation strategy to select an imputation method for mixed-type trait data
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Leveraging a global, rederated, real-world data network to optimize investigator-initiated pediatric clinical trials: The TriNetX Pediatric Collaboratory Network
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Data from: Predicting habitat suitability and connectivity for management and conservation of urban wildlife: A real-time web application for grassland water voles
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Data from: Real-time imaging of rotation during synthesis by the replisome
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For the people by the people: citizen science web interface for real-time monitoring of tick risk areas in Finland
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Risk factors for cardiovascular disease (CVD) in adults with type 1 diabetes: findings from prospective real-life T1D exchange registry
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Spatiotemporal processing of real faces is supported by dissociable visual-sensing-modulated neural circuitry
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Clinical surveillance identifies SARS-CoV-2 outbreaks and emergence of novel variants in real-time
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Data from: Neural responses to kills/deaths in real MOBA games are associated with addiction-related traits and subjective pleasant/unpleasant experiences
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Location Location Location: Survival of Antarctic biota requires the best real-estate
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Data from: Hippocampal replay of experience at real-world speeds
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ZipSeq : barcoding for real-time mapping of single cell transcriptomes
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S-BLE: A participatory BLE sensory data set recorded from real-world bus travel events
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Seismic datasets in "Real-time earthquake location based on the Kalman filter formulation"
<p>Synthetic seismic dataset and Parkfield seismic dataset that used in the manuscript entitled "Real-time earthquake location based on the Kalman filter formulation" submitted to Geophysical Research Letters</p>
Data from: A novel real-world ecotoxicological dataset of pelagic microbial community responses to wastewater
<p>Real-world observational datasets that record and quantify pressure-stressor-response linkages between effluent discharges and natural aquatic systems are rare. With global wastewater volumes increasing at unprecedented rates, it is urgent that the present dataset is available to provide the necessary information about microbial community structure and functioning. Field studies were performed at two time-points in the Austral summer. Single-species and microbial community whole effluent toxicity (WET) testing was performed at a complete range of effluent concentrations and two salinities, with accompanying environmental data to provide new insights into nutrient and organic matter cycling, and to identify ecotoxicological tipping points. The two salinity regimes were chosen to investigate future scenarios based on a predicted salinity increase at the study site, typical of coastal regions with rising sea levels globally. Flow cytometry, amplicon sequencing of 16S and 18S rRNA genes and micro-fluidic quantitative polymerase-chain reactions (MFQPCR) were used to determine chlorophyll-a and total bacterial cell numbers and size, as well as taxonomic and functional diversity of pelagic microbial communities. This strong pilot dataset could be replicated in other regions globally and would be of high value to scientists and engineers to support the next advances in microbial ecotoxicology, environmental biomonitoring and estuarine water quality modelling.</p>
CURE-TSR: Challenging Unreal and Real Environments for Traffic Sign Recognition
<p>As one of the research directions at <a href="https://ghassanalregib.info/">OLIVES Lab @ Georgia Tech</a>, we focus on the robustness of data-driven algorithms under diverse challenging conditions where trained models can possibly be depolyed. To achieve this goal, we introduced a large-sacle (>2M images) traffic sign recognition dataset (<a href="https://github.com/olivesgatech/CURE-TSR">CURE-TSR</a>) which is among the most comprehensive datasets with controlled synthetic challenging conditions. Traffic sign images in the <a href="https://github.com/olivesgatech/CURE-TSR">CURE-TSR</a> dataset were cropped from the <a href="https://github.com/olivesgatech/CURE-TSD">CURE-TSD</a> dataset, which includes around 1.7 million real-world and simulator images with more than 2 million traffic sign instances. Real-world images were obtained from the BelgiumTS video sequences and simulated images were generated with the Unreal Engine 4 game development tool. Sign types include speed limit, goods vehicles, no overtaking, no stopping, no parking, stop, bicycle, hump, no left, no right, priority to, no entry, yield, and parking. Unreal and real sequences were processed with state-of-the-art visual effect software Adobe(c) After Effects to simulate challenging conditions, which include rain, snow, haze, shadow, darkness, brightness, blurriness, dirtiness, colorlessness, sensor and codec errors. Please refer to our <a href="https://github.com/olivesgatech/CURE-TSR">GitHub page</a> for code, papers, and more information.</p> <p>Instructions: </p> <p>The name format of the provided images are as follows: "sequenceType_signType_challengeType_challengeLevel_Index.bmp"</p> <ul> <li> <p>sequenceType: 01 - Real data 02 - Unreal data</p> </li> <li> <p>signType: 01 - speed_limit 02 - goods_vehicles 03 - no_overtaking 04 - no_stopping 05 - no_parking 06 - stop 07 - bicycle 08 - hump 09 - no_left 10 - no_right 11 - priority_to 12 - no_entry 13 - yield 14 - parking</p> </li> <li> <p>challengeType: 00 - No challenge 01 - Decolorization 02 - Lens blur 03 - Codec error 04 - Darkening 05 - Dirty lens 06 - Exposure 07 - Gaussian blur 08 - Noise 09 - Rain 10 - Shadow 11 - Snow 12 - Haze</p> </li> <li> <p>challengeLevel: A number in between [01-05] where 01 is the least severe and 05 is the most severe challenge.</p> </li> <li> <p>Index: A number shows different instances of traffic signs in the same conditions.</p> </li> </ul>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.