Data · dataset · 2021
MoLa RGB CovSurv
Listed in Teesside University Research Data Repository
This repository presents one of the datasets described in the article "AI based monitoring of different risk levels in Covid19 context", published in the Multidisciplinary Digital Publishing Institute special issue "Human Activity Recognition Based on Image Sensors and Deep Learning".
Description
The repository includes the complete dataset used for the training, validation and testing tasks, in order to detect the presence or absence of mask by people in public areas.
There are two different folders: images and labels, each divided in three different subdatasets (train, valid, test). For each image, there is a text document with the exactly same name, where is present the information about each object (in this case, people's faces). This labels information uses the class associated to the object (0: With_Mask and 1: Without_Mask), and the correspondent normalized values of the bounding box of the face (x_center, y_center, width, height).
Links
Where it is published
- DOI doi.org/10.17632/vzf939jbxy.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Deep learning · Earth & Environmental Science · Engineering · Homo sapiens · Humanities · Life Sciences · Medicine & Health · Social Science
Provenance · 1 source records, 16 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/vzf939jbxy.1 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:461103 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Deep Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:text | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[organism].NCBITaxon:9606 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Human'] |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |