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11 results for “information loss”
ExpertSegmentation: Sample datasets for segmentation of microscopy with domain-informed targets via custom loss
<p>Sample datasets for submission to NeurIPS 2024 titled ExpertSegmentation: Segmentation for microscopy with domain-informed targets via custom loss. Hand-labels were generated using Ilastik. Files include:</p> <ol> <li><strong>NMC_3D</strong>: 3D, 2-phase, microCT image of a Lithium-ion battery LiNiMnCoO2 electrode</li> <li><strong>NMC_3D_Labels: </strong>Hand labels for NMC_3D volume.</li> <li><strong>NMC_2D</strong>: 2D, 4-phase, SEM image of a Lithium-ion battery LiNiMnCoO2 electrode cross-section</li> <li><strong>NMC_2D_Labels: </strong>Hand labels for NMC_2D image.</li> <li><strong>Graphite_3D</strong>: 3D, 3-phase, microCT image of a Laser-ablated lithium-ion battery graphite electrode</li> <li><strong>Graphite_3D_Labels: </strong>Hand labels for Graphite_3D volume.</li> <li><strong>PEMFC_3D</strong>: 3D, 5-phase, microCT image of a Polymer Electrolyte Membrane Fuel Cell (PEMFC)</li> <li><strong>PEMFC_3D_Labels: </strong>Hand labels for PEMFC_3D volume.</li> </ol> <p>See references for dataset sources.</p>
Datasets for input and output of INFORM Severity-based SMAA study of resource allocation in humanitarian aid and disaster management under climatic losses and damages
<p>The landscape of climate change and extreme events will remain a wicked problem for equitable and forward-looking resource prioritisation. The question of how to couple climate and multi-risk information remains. IPCC has considered that multi-criteria decision analysis (MCDA) can help.</p> <p>We use stochastic multi-attribute analysis (SMAA), a variant of MCDA, to compute prioritisations of climatic losses & damages (l&d) for fragile countries with a humanitarian response plan. SMAA is combined with the INFORM Severity index, measuring the status of crises and disasters, and preferences gathered from stakeholders (e.g., United Nations, European Union, World Bank, the research and public sector, civil society).</p> <ul> <li><strong>Dataset S1. </strong>XLS-file with all the input data compiled from sources, concurrent data manipulation, and descriptions of steps taken until ready for the SMAA.</li> <li><strong>Dataset S2.</strong> XLS-file with results of the SMAA for all weight schemes and concurrent analysis, such as sensitivity heat mapping, correlations, regressions, and Tukey mean-difference plot.</li> </ul>
FIGURE 1. A in A novel distance that reduces information loss in continuous characters with few observations
FIGURE 1. A. An interval and its components; B. Possible relationships between two intervals and A, B, and C in the Character X's space; C. DBI's behavior according to the possible relationships between the intervals of any two objects. For this, a mobile test interval of range X with its upper limit placed at Y was discreetly displaced by D units W times. For each of these W steps the DBI between the test interval and a fixed interval of range F with its lower limit placed at H were computed. The Left section shows the DBI for non-overlapped intervals; the Central section shows the DBI for partially overlapped intervals; and the Right section shows the DBI for fully overlapped intervals. Dashed lines show the results between intervals with different relative ranges (i.e., interval sizes). The asterisks show the paired distances between A, B, and C using DBI.
Supplementary information for: From scales to armour: scale losses and trunk bony plate gains in ray-finned fishes
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Dataset for a physics informed deep learning method with adaptively weighted loss for modeling soil water flows
<p>The data for the 11 scenarios generated by Hydrus-1D is located in data.zip</p> <p>The code for the physics-informed neural networks with adaptively weighted loss used to simulate water flow in loam soils is located at PINN_adaptively_weighted_loss_loam.zip</p>
Promoting Successful Weight Loss in Primary Care in Louisiana Using Information Technology
ClinicalTrials.gov study NCT05523375. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Tuning Geometric Morphometrics: an R tool to reduce information loss caused by surface smoothing
The application of Geometric Morphometrics has remarkably increased since 3D imaging techniques have become widespread, such as high-resolution computerised tomography, laser scanning and photogrammetry. Acquisition, 3D rendering and simplification of virtual objects produce faceting and topological artefacts, which can be counteracted by applying decimation and smoothing algorithms. Nevertheless, smoothing algorithms can have detrimental effects. This work aims at developing a method to assess the amount of information loss or recovery after the application of 3D surface smoothing. The method presented here is conceived to optimise the smoothing procedure for 3D surfaces used in Geometric Morphometrics. We implemented the method in a tool running in the r statistical environment. The tool requires one surface, one landmark set and one surface semilandmark set to estimate the best smoothing settings, including algorithm type, iteration and scale factor value. Additional parameters can be tuned by the user. We describe the method in detail, reporting the tool usage, including its main settable parameters. One example is provided as a further explanation of the method. Our method reduces the chances of losing information in Geometric Morphometrics applications and is a unique attempt of standardising a widespread, potentially damaging procedure. The tool represents an advance in the application of Geometric Morphometrics.
Efficiently characterizing quantum information flow, loss and recovery in the central spin system
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Wayfinding Information Access System for People With Vision Loss
ClinicalTrials.gov study NCT00829036. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Emergency Egress and Information System for Persons With Vision Loss
ClinicalTrials.gov study NCT00262509. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Tuning Geometric Morphometrics: an R tool to reduce information loss caused by surface smoothing
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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.