MYNursingHome: A fully-labelled image dataset for indoor object classification.
Deep learning
Image dataset
Indoor objects
Object classification
Object detection
Journal
Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995
Informations de publication
Date de publication:
Oct 2020
Oct 2020
Historique:
received:
17
07
2020
revised:
19
08
2020
accepted:
28
08
2020
entrez:
28
9
2020
pubmed:
29
9
2020
medline:
29
9
2020
Statut:
epublish
Résumé
A fully labelled image dataset serves as a valuable tool for reproducible research inquiries and data processing in various computational areas, such as machine learning, computer vision, artificial intelligence and deep learning. Today's research on ageing is intended to increase awareness on research results and their applications to assist public and private sectors in selecting the right equipments for the elderlies. Many researches related to development of support devices and care equipment had been done to improve the elderly's quality of life. Indoor object detection and classification for autonomous systems require large annotated indoor images for training and testing of smart computer vision applications. This dataset entitled MYNursingHome is an image dataset for commonly used objects surrounding the elderlies in their home cares. Researchers may use this data to build up a recognition aid for the elderlies. This dataset was collected from several nursing homes in Malaysia comprises 37,500 digital images from 25 different indoor object categories including basket bin, bed, bench, cabinet and others.
Identifiants
pubmed: 32984464
doi: 10.1016/j.dib.2020.106268
pii: S2352-3409(20)31162-8
pmc: PMC7494477
doi:
Types de publication
Journal Article
Langues
eng
Pagination
106268Informations de copyright
© 2020 The Authors.
Déclaration de conflit d'intérêts
None.
Références
Sensors (Basel). 2017 Nov 16;17(11):
pubmed: 29144395