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126 results for “face masks”
NII Face Mask Dataset
<p>=====================================================================<br> # NII Face Mask Dataset v1.0<br> =====================================================================</p> <p>Authors:<br> Trung-Nghia Le (1), Khanh-Duy Nguyen (2), Huy H. Nguyen (1), Junichi Yamagishi (1), Isao Echizen (1)</p> <p>Affiliations:<br> (1)National Institute of Informatics, Japan <br> (2)University of Information Technology-VNUHCM, Vietnam</p> <p>National Institute of Informatics <br> Copyright (c) 2021</p> <p>Emails:<br> {ltnghia, nhhuy, jyamagis, iechizen}@nii.ac.jp, {khanhd}@uit.edu.vn</p> <p>Arxiv: https://arxiv.org/abs/2111.12888<br> NII Face Mask Dataset v1.0: https://zenodo.org/record/5761725</p> <p>=============================== INTRODUCTION ===============================</p> <p>The NII Face Mask Dataset is the first large-scale dataset targeting mask-wearing ratio estimation in street cameras. This dataset contains 581,108 face annotations extracted from 18,088 video frames (1920x1080 pixels) in 17 street-view videos obtained from the Rambalac's YouTube channel.</p> <p>- https://www.youtube.com/c/Rambalac</p> <p>The videos were taken in multiple places, at various times, before and during the COVID-19 pandemic. The total length of the videos is approximately 56 hours.</p> <p><br> =============================== REFERENCES ===============================</p> <p>If your publish using any of the data in this dataset please cite the following papers:</p> <p>#Pre-print version<br> @article{Nguyen202112888,<br> title={Effectiveness of Detection-based and Regression-based Approaches for Estimating Mask-Wearing Ratio},<br> author={Nguyen, Khanh-Duy and Nguyen, Huy H and Le, Trung-Nghia and Yamagishi, Junichi and Echizen, Isao},<br> archivePrefix={arXiv},<br> arxivId={2111.12888},<br> url={https://arxiv.org/abs/2111.12888},<br> year={2021}<br> }</p> <p>#Final version<br> @INPROCEEDINGS{Nguyen2021EstMaskWearing,<br> author={Nguyen, Khanh-Duv and Nguyen, Huv H. and Le, Trung-Nghia and Yamagishi, Junichi and Echizen, Isao},<br> booktitle={2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)}, <br> title={Effectiveness of Detection-based and Regression-based Approaches for Estimating Mask-Wearing Ratio}, <br> year={2021},<br> pages={1-8},<br> url={https://ieeexplore.ieee.org/document/9667046},<br> doi={10.1109/FG52635.2021.9667046}}</p> <p><br> ======================== DATA STRUCTURE ==================================</p> <p><br> 1. Directory Structure<br> -------------------------------</p> <p>./NFM<br> ├── dataset<br> │ ├── train.csv: annotations for the train set.<br> │ ├── test.csv: annotations for the test set.<br> └── README_v1.0.md</p> <p><br> 2. Description for each files in detail.<br> ---------------------------------------------------------</p> <p>We use the same structure for two CSV files (train.csv and test.csv). Both CSV files have the same columns:<br> <1st column>: video_id (a source video can be found by following the link: https://www.youtube.com/watch?v=<video_id>)<br> <2nd column>: frame_id (the index of a frame extracted from the source video)<br> <3rd column>: timestamp in milisecond (the timestamp of a frame extracted from the source video)<br> <4th column>: label (for each annotated face, one of three labels was attached with a bounding box: 'Mask'/'No-Mask'/'Unknown')<br> <5th column>: left<br> <6th column>: top<br> <7th column>: right<br> <8th column>: bottom<br> Four coordinates (left, top, right, bottom) were used to denote a face's bounding box. </p> <p><br> ============================== COPYING ================================</p> <p>This repository is made available under Creative Commons Attribution License (CC-BY). </p> <p>Regarding Creative Commons License: Attribution 4.0 International (CC BY 4.0), <br> please see https://creativecommons.org/licenses/by/4.0/</p> <p>THIS DATABASE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND <br> ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED <br> WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. <br> IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, <br> INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, <br> BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, <br> OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, <br> WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) <br> ARISING IN ANY WAY OUT OF THE USE OF THIS DATABASE, EVEN IF ADVISED OF THE <br> POSSIBILITY OF SUCH DAMAGE</p> <p><br> ====================== ACKNOWLEDGEMENTS ================================</p> <p>This research was partly supported by JSPS KAKENHI Grants (JP16H06302, JP18H04120, JP21H04907, JP20K23355, JP21K18023), and JST CREST Grants (JPMJCR20D3, JPMJCR18A6), Japan.</p> <p>This dataset is based on the Rambalac's YouTube channel: https://www.youtube.com/c/Rambalac<br> </p>
Respiratory virus shedding in exhaled breath and efficacy of face masks
<p>We identified seasonal human coronaviruses, influenza viruses and rhinoviruses in the exhaled breath and coughs of children and adults with acute respiratory illness. Surgical face masks significantly reduced detection of influenza virus RNA in respiratory droplets and coronavirus RNA in aerosols, with a marginally significant reduction in coronavirus RNA in respiratory droplets. Our results indicate that surgical facemasks could prevent transmission of human coronaviruses and influenza viruses from symptomatic individuals.</p>
HIGH Lentäjän kasvosuojus Cold Weather Face Mask
Yhdysvaltain ilmavoimien D-1A -kasvosuojus. Se oli suomalaisen retkikunnan käytössä tutkimusmatkalla, joka tehtiin keväällä 1966 Grönlannin jäätikköalueelle. Helsingin Sanomat oli yksi hankkeen rahoittajista ja lehdessä julkaistiin runsaasti kirjoituksia ryhmän matkavalmisteluista, matkasta ja kotiinpaluusta. Kasvosuojain oli retkikuntaan kuuluneen Peter Bouchtin käytössä. A D-1A face mask of the US air force. This mask was used by a Finnish expedition to the glaciers of Greenland in the spring of 1966. Helsingin Sanomat was one of the financiers of the expedition and the newspaper published many stories about how the group prepared for the expedition, the journey itself and the group's homecoming. The face mask was used by expedition member Peter Boucht. The object (pm766) and 3D model: Päivälehti Museum, Finland (member of Traffic Museums Association). The photogrammetric 3D model may include touch-ups and modelled additions. Source: Objaverse 1.0 / Sketchfab
Face Mask
Face Mask Scanned by Thunk3D Handheld Scanner fisher Contact me for more information. Whatsapp/phone/wechat: +86 18518781107 Email:daicy@thunk3d.com Facebook:www.facebook.com/qinqin.li.77 Linkedin: https://www.linkedin.com/in/daicy-li-399b82119/ Titter: https://twitter.com/DaicyLi Source: Objaverse 1.0 / Sketchfab
decorative face mask
this model craeted in rhino 6 and rendered by keyshot. it can be used for cnc or decorative purposes. no naked edges and closed meshes. Source: Objaverse 1.0 / Sketchfab
Buddha Face Mask
This is a wooden Buddha face mask that I bought on a trip to China in 2006. The scan was made in 2019 using an Artec Space Spider handheld 3D scanner. The scan was cleaned up using Zbrush and Photoshop. Source: Objaverse 1.0 / Sketchfab
Engineering surgical face masks with photothermal and photodynamic plasmonic nanostructures for enhancing filtration and on-demand pathogen eradication_[photothermal properties]
<p>Engineering surgical face masks with photothermal and photodynamic plasmonic nanostructures for enhancing filtration and on-demand pathogen eradication: photothermal properties</p>
Baule People Double Face Ceremonial Dance Mask
This mask comes from the Baule people of Cote D'Ivoire. Carved wood with encrusted dark brown black and red patina in the form of two faces side by side, one being black (right) and the other red (left) with fine facial details & scarification, pair of horns atop each face, edged with zigzag motif of the Goli Society and 2 handle-like projections at base, pair of eye openings. Source: Objaverse 1.0 / Sketchfab
Face Mask
Face masks protect the wearer's nose and mouth from contact with droplets that may contain germs. Source: Objaverse 1.0 / Sketchfab
Angry Face / Mask Relief - photogrammetry
A sculpture of an angry face/mask in Prison Tower and Torture Chamber in Gdańsk. Photogrammetry model created from 47 photos made with phone camera (iPhone 11) - had some issues in 3df Zephyr with the model scale, but in the end it was managable and I was able to create this mid-level polygon model. Source: Objaverse 1.0 / Sketchfab
Face mask detection and masked facial recognition dataset (MDMFR Dataset)
<p>The unavailability of a unified standard dataset for face mask detection and masked facial recognition motivated us to develop an in-house MDMFR dataset (<a href="https://www.sciencedirect.com/science/article/pii/S1319157821003633#b0170">MDMFR, 2022</a>) to measure the performance of face mask detection and masked facial recognition methods. Both of these tasks have different dataset requirements. Face mask detection requires the images of multiple persons with and without mask. Whereas, masked face recognition requires multiple masked face images of the same person. Our MDMFR dataset consists of two main collections, 1) face mask detection, and 2) masked facial recognition. There are 6006 images in our MDMFR dataset. The face mask detection collection contains two categories of face images i.e., mask and unmask. Our detection database consists of 3174 with mask and 2832 without mask (unmasked) images. To construct the dataset, we captured multiple images of the same person in two configurations (mask and without mask). The masked facial recognition collection contains a total of 2896 masked images of 226 persons. More specifically, our dataset includes the images of both male and female persons of all ages including the children. The images of our dataset are diverse in terms of gender, race, and age of users, types of masks, <a href="https://www.sciencedirect.com/topics/computer-science/illumination-condition">illumination conditions</a>, face angles, occlusions, environment, format, dimensions, and size, etc. Before being fed to our DeepMaskNet model, all images are scaled to a width and height of 256 pixels. All images have a bit depth of 24. We prepared the images of our dataset for the proposed DeepMaskNet model during preprocessing where images are cropped in Adobe-Photoshop to exclude the extra information like neck and shoulder. As the input size of our Deepmasknet model was 256-by-256, so images were resized to 256-by-256 in publicly available Plastiliq Image Resizer software (<a href="https://www.sciencedirect.com/science/article/pii/S1319157821003633#b0215">Plastiliq, 2022</a>).</p>
Masked datasets from an fMRI experiment on the impact of semantic priming on the perception of ambivalent (male versus female) faces
<p>Twenty-four female native Dutch speakers participated in the fMRI experiment and gained monetary compensation for their participation. Only female participants were recruited for the study, in order to avoid gender-related confounding factors. The study was approved by the local ethics committee (CMO Arnhem-Nijmegen, Radboud University Medical Center, ethical approval for studies on healthy human subjects at the Donders Centre for Cognitive Neuroimaging, no ECG 2012-0910-058) and conducted in accordance with their guidelines. All participants signed informed consent forms before the experiment. The data from seven subjects were excluded from the analysis: 3 subjects failed to finish the task and 4 subjects exhibited head motion that exceeded the maximum acceptance rate of 2 [mm]. The remaining 17 subjects (females, age 18-29 years) reported no neurological diseases, and had normal or corrected-to-normal vision. </p> <p>A set of realistic 3D faces was morphed across gender (from extremely female to extremely male) using FaceGen Modeller 3.5 (Singular Inversions, www.facegen.com). The morphing procedure started from 40 distinct faces. For each face, we gradually modulated gender features in 5 steps with the same amount of feature transformation in each step. The face stimuli were presented frontally and cropped around the oval of the face. We controlled for luminance using SHINE toolbox for MATLAB. The perceptual boundary within gender continuum of faces was established in a separate behavioral experiment.</p> <p>Each trial started with priming: presentation of a gender-related word 'man' or 'vrouw' for 0.2 [s]. Then, after the fixation cross 0.25 [s]), a face was presented (0.5 [s]), followed by an inter-trial period of a randomized length of 5-7 [s]. Participants were asked to perform a matching task: respond 'yes' if a word and subsequent picture corresponded in gender, and 'no' otherwise. The experiment was carried out in Dutch. The buttons were counterbalanced across subjects. The experiment was divided into 6 blocks in order to avoid fatigue. Each block consisted of 50 trials. The order of stimuli was randomized across blocks and participants. We used Presentation software (version 17.1, www.neurobs.com) in order to screen the stimuli during the experiment.</p> <p>Functional images were acquired using 3T Skyra MRI system (Siemens Magnetom), T2* weighted echo-planar images (gradient-echo, repetition-time TR = 1760 [ms], echo-time TE = 32 [ms], 0.7 [ms] echo spacing, 1626 hz/Px bandwidth, generalized auto-calibrating partially parallel acquisition (GRAPPA), acceleration factor 3, 32 channel brain receiver coil). In total, 78 axial slices were acquired (2.0 [mm] thickness, 2.0*2.0 [mm] in plane resolution, 212 [mm] field of view (FOV) whole brain, anterior-to-posterior phase-encoding direction).</p> <p>The data reprocessing was performed using SPM12 (Welcome Trust Center for Neuroimaging, University College London, UK). Functional scans were realigned to the first scan of the first run with further realignment to the mean scan. We performed slice-time correction on realigned images to account for differences in image acquisition between slices. Motion-related components were removed from the data using a data-driven ICA-AROMA. Denoised functional scans were spatially normalized to the Montreal Neurological Institute (MNI) space without changing the voxel size. Normalized data were smoothed spatially with a Gaussian kernel of 6 [mm] full-width at half-maximum.</p> <p>We extracted region-of-interest (ROI) mask using Anatomical Automatic Labeling atlas (AAL). According to our a priori hypothesis, we preselected the bilateral SPL (4288 voxels) and the bilateral IPL (3792 voxels).</p>
Electrocharging face masks with corona discharge treatment
<p></p><p>We detail an experimental method to electrocharge N95 facepiece respirators and face masks (FMs) made from a variety of fabrics (including non-woven polymer and knitted cloth) using corona discharge treatment (CDT). We present practical designs to construct a CDT system from commonly available parts and detail calibrations performed on different fabrics to study their electrocharging characteristics. After confirming the post-CDT structural integrity of fabrics, measurements showed that all non-woven polymer electret and only some knitted cloth fabrics are capable of charge retention. Whereas polymeric fabrics follow the well-known isothermal charging route, ion adsorption causes electrocharging in knitted cloth fabrics. Filtration tests demonstrate improved steady filtration efficiency in non-woven polymer electret filters. On the other hand, knitted cloth fabric filters capable of charge retention start with improved filtration efficiency which decays in time over up to 7 h depending on the fabric type, with filtration efficiency tracking the electric discharge. A rapid recharge for a few seconds ensures FM reuse over multiple cycles without degradation.</p><p></p>
Data of cerebral and systemic physiological parameters while wearing face masks
<p>This repository contains two data sets and two R codes.</p> <p>- Fischer_et_al_Data_masks_group_average_time_plot.txt: contains the group average data over time of two groups wearing different face masks. The corresponding R code to create plots of the data over time is the file Fischer_et_al_Masks_plot_group_average_time.R</p> <p>- Fischer_et_al_Data_masks_lme_analysis.txt: contains average data for baseline (no mask) and average data of a period where a face mask was worn for each subject. Each subject was measured twice with two different mask types. The corresponding R code to analyze the data for the effect of wearing a mask on the different parameters can be done with the file Fischer_et_al_Masks_LME_analysis.R</p>
Men-yoroi Demon samurai armor face mask scan
https://en.wikipedia.org/wiki/Men-yoroi Scan by austinbeaulier austinbeulier.com Check out more scans on my page. Source: Objaverse 1.0 / Sketchfab
Comparison of High Flow Nasal Cannula and Standard Face Mask Oxygen Therapy in Children With Bronchiolitis
ClinicalTrials.gov study NCT04245202. IPD Sharing: Not stated. Countries: 1. Publications: 13.
Effect of Head Rotation on Efficacy of Face Mask Ventilation in Anesthetized Obese (BMI ≥ 35) Adults
ClinicalTrials.gov study NCT03876873. IPD Sharing: NO. Countries: 1. Publications: 5.
Routine Or Selective Application of a Face Mask for Preterm Infants at Birth: the ROSA Trial
ClinicalTrials.gov study NCT04500353. IPD Sharing: YES. Countries: 1. Publications: 14.
Mask Ventilation With Different Face Masks During Neonatal Resuscitation
ClinicalTrials.gov study NCT01685697. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Evaluation Of The Total Face Mask For Emergency Application In Acute Respiratory Failure
ClinicalTrials.gov study NCT00686257. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ScienceDex guides
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Allen Brain Atlas
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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.