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3 results for “Face mask detection”
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>
Investigation of the Accordance Between Event Detection of prismaLINE Devices and Polysomnography Using Full Face Masks
ClinicalTrials.gov study NCT06317077. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Face Mask Detection Dataset
<p>The dataset contains real images of people with face mask and without face mask. Each class contains 150 images.</p> <p>Cite us:</p> <p>Ferdib-Al-Islam, Suprio Sarkar, Nusrat Jahan and Farjana Yeasmin Rupa, “Face Mask Detection Dataset”. Zenodo, Jul. 15, 2021. doi: 10.5281/zenodo.5305989</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.