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46 results for “unsupervised learning”

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zenodo28/100

Support videos for the article "Damage categorization in full-scale, full-composite ship hull under high-energy impacts by unsupervised-learning-enabled acoustic emission monitoring and laser shearography inspection"

<p>Video 1: Video showing one of the impact from a general perspective</p> <p>Video 2: Slow-motion video of the second impact</p>

opencc-by-nc-nd-4.0Jun 2024View details →
zenodo28/100

Unsupervised behaviour analysis and magnification (uBAM) using deep learning Dataset

<h3>Abstract</h3> <p>Motor behaviour analysis is essential to biomedical research and clinical diagnostics as it provides a non-invasive strategy for identifying motor impairment and its change caused by interventions. State-of-the-art instrumented movement analysis is time- and cost-intensive, because it requires the placement of physical or virtual markers. As well as the effort required for marking the keypoints or annotations necessary for training or fine-tuning a detector, users need to know the interesting behaviour beforehand to provide meaningful keypoints. Here, we introduce unsupervised behaviour analysis and magnification (uBAM), an automatic deep learning algorithm for analysing behaviour by discovering and magnifying deviations. A central aspect is unsupervised learning of posture and behaviour representations to enable an objective comparison of movement. Besides discovering and quantifying deviations in behaviour, we also propose a generative model for visually magnifying subtle behaviour differences directly in a video without requiring a detour via keypoints or annotations. Essential for this magnifica-tion of deviations, even across different individuals, is a disentangling of appearance and behaviour. Evaluations on rodents and human patients with neurological diseases demonstrate the wide applicability of our approach. Moreover, combining optoge-netic stimulation with our unsupervised behaviour analysis shows its suitability as a non-invasive diagnostic tool correlating function to brain plasticity</p> <div>&nbsp;</div> <div> <p>&nbsp;</p> </div>

openApr 2021View details →
zenodo28/100

Data for "Defect detection in atomic-resolution images via unsupervised learning with translational invariance"

<p>This&nbsp;dataset accompanies the paper titled&nbsp;<em>Defect detection in atomic-resolution images via unsupervised learning with translational invariance</em>&nbsp;by&nbsp;Yueming Guo<sup>*</sup>, Sergei V. Kalinin, Hui Cai, Kai Xiao, Sergiy Krylyuk, Albert V Davydov, Qianying Guo, Andrew R. Lupini<sup>* </sup></p>

opencc-by-4.0Sep 2021View details →
ClinicalTrials.gov28/100

Unsupervised Machine Learning for Clustering of Septic Patients to Determine Optimal Treatment

ClinicalTrials.gov study NCT03752489. IPD Sharing: Not stated. Countries: 0. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

COVID-19 Clinical Status Associated With Outcome Severity: An Unsupervised Machine Learning Approach

ClinicalTrials.gov study NCT05119465. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
dryad24/100

Data from: The use of an unsupervised learning approach for characterizing latent behaviors in accelerometer data

Open the record for dataset details and reuse information.

publicDec 2016View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record