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Dataset results
7 results for “information fusion”
Applying Sensor Fusion to Augment Hyperspectral Data with Depth Information
<p>The research data for the paper "Applying Sensor Fusion to Augment Hyperspectral Data with Depth Information"<br> <br> Data in the archive "hyperdepth.tar.gz" includes:</p> <p><br> <strong>calibration_images/</strong><br> includes preprocessed images for calibrating both cameras</p> <p><strong>pointclouds/</strong><br> Includes individual hyperspectral point clouds for each view (front, rightmost, right, leftmost, left with postfixes correspondingly: edesta, oikea, oikea2, vasen, vasen2)<br> <br> <strong>raw_images/</strong><br> Two directories "day5" and "day6" which include the raw hyperspectral images and kinect images<br> <br> Some extra images are included which were not used in the research paper.</p> <p> </p> <p><strong>2022-03-11_112336_stereocalibration.json</strong> includes calibration results (mainly the intrinsic camera matrix and extrinsic parameters) for the setup.</p>
Data for "Using physics-informed neural networks to predict the lifetime of laser powder bed fusion processed 316L stainless steel under multiaxial low-cycle fatigue loading"
<p>Title of dataset: Data for "Using physics-informed neural networks to predict the lifetime of laser powder bed fusion processed 316L stainless steel under multiaxial low-cycle fatigue loading".</p> <p>Name/institution/contact information: Dr. Michal Bartošák, Czech Technical University in Prague - Faculty of Mechanical Engineering, email: michal.bartosak@fs.cvut.cz.</p> <p>Date of data collection: The data were collected between 2021 and 2024.</p> <p>File name structure: The data consists of two files: "316L_fatigue_and_defects.xls," which contains fatigue lifetime data and defect characteristics, and an associated description file, "read_me.txt."</p> <p>See "https://doi.org/10.1016/j.ijfatigue.2024.108608" for the associated article and a detailed description of the methods.</p>
Fine-grained classification of journal articles by relying on multiple layers of information through similarity network fusion: the case of the Cambridge Journal of Economics
<p>prova</p>
Multi year social stability and social information use in reef sharks with diel fission-fusion dynamics: Raw acoustic detection
<p><span>Animals across vertebrate taxa form social communities and often exist as fission-fusion societies. Central place foragers (CPF) may form social groups, from which they will predictably disperse to forage, either individually or in smaller groups, before returning to fuse with the larger group. However, the function and stability of social associations in predatory fish acting as CPFs is unknown, as individuals do not need to return to a shelter, yet show fidelity to core areas. Using dynamic social networks generated from acoustic tracking data, we document spatially structured sociality in CPF grey reef sharks at a Pacific Ocean atoll. We show that sharks form stable, social groups over multi-year periods, with some dyadic associations consistent for up to four years. Groups primarily formed during the day, increasing in group size before sharks dispersed from the reef to forage at night. Our simulations suggest that multiple individuals sharing a central place and using social information while foraging (i.e. local enhancement), will outperform non-CPF social foragers. We show multiyear social stability in sharks and suggest that social foraging with information transfer could provide a generalisable mechanism for the emergence of sociality with group central place foraging.</span></p>
Multi year social stability and social information use in reef sharks with diel fission-fusion dynamics: Raw acoustic detection
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Development and Demonstration of Intelligent Assessment Based on Multi-modal Information Fusion for Tumor Risk and Diagnosis and Treatment
ClinicalTrials.gov study NCT06653478. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Multimodal Tongue-Pulse Information Fusion for Syndrome Diagnosis and Cohort Study in Children With Asthma
ClinicalTrials.gov study NCT07383883. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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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.