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8 results for “digital augmentation”
Data Augmentation for learning mechanical digital twins of voids in welding joints
<p>In Source-2_Data_Augmentation:</p> <p>Exercice1_augmentation.ipynb Jupyter Notebook for data warpping of defect images.</p> <p>Exercice2_augmentation_multimodale.ipynb Jupyter Notebook for multimodal data augmentaion (defect images and mechanical fields) via oversampling</p> <p>Exercice3_clustering.ipynb Data clustering using the k-medoids algorithm applied to mechanical dissimilarity of the defects.</p> <p>k_medoids.py is a python code of a kmedoids algorithm.</p> <p>in Data:</p> <p>All_images.npy (numpy file) contains the defect images.</p> <p>All_Stresses.npy (numpy) contains mechanical fields, All_Stresses[k,i,j,ic,it] is the instance number k of the component ic of the Cauchy stress tensor at time it. The mechanical problem is decribed in <a href="https://dx.doi.org/10.5802/crmeca.51">⟨10.5802/crmeca.51⟩</a>. <a href="https://hal.archives-ouvertes.fr/hal-03113503">⟨hal-03113503⟩.</a></p> <p>New_images_1.npy and New_Stresses_1.npy are augmented data for k=1.</p> <p>New_images_87.npy and New_Stresses_87.npy are augmented data for k=87.</p> <p>Dissimilarity_Stress.npy is the Frobenius norm of the distances between stress tensors (All_Stresses.npy).</p> <p> </p>
Dataset for damage-augmented digital twins towards the automated inspection of buildings
<p>This repository contains the dataset used for computing damage augmented digital twins for buildings via image-based approach. The method that uses this data set was presented in the paper "Damage-augmented digital twins towards the automated inspection of buildings" by Pantoja-Rosero et., al. (2023)" https://doi.org/10.1016/j.autcon.2023.104842</p> <p> </p> <p> </p> <p> </p>
Comparing Insomnia Care As Usual to Digital Augmentation (CICADA)
ClinicalTrials.gov study NCT05490550. IPD Sharing: NO. Countries: 1. Publications: 3.
Evaluation of Nutrition Training Augmented With Digital Technology in Graduate Medical Education
ClinicalTrials.gov study NCT06088251. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Augmented Reality-Assisted Bonding Versus Digitally-Assisted Indirect Bonding in Orthodontic Patients
ClinicalTrials.gov study NCT04658446. IPD Sharing: NO. Countries: 0. Publications: 3.
Comparison of Stationary Breast Tomosynthesis and 2-D Digital Mammography in Patients With Breast Augmentation
ClinicalTrials.gov study NCT02008032. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Digital Rehabilitation Environment Augmenting Medical System
ClinicalTrials.gov study NCT03385993. IPD Sharing: NO. Countries: 1. Publications: 0.
Comparative Efficacy of Novel Transcranial Random Noise Stimulation Versus Direct Current Stimulation on Augmenting Digital Mirror Therapy in Chronic Stroke
ClinicalTrials.gov study NCT05733858. IPD Sharing: Not stated. Countries: 0. 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.
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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.