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MYNursingHome: a fully-labelled image dataset for indoor object classification

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...

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Main Authors: Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi
Format: Article
Language:English
Published: Elsevier 2020
Online Access:http://psasir.upm.edu.my/id/eprint/86874/1/MYNursingHome.pdf
http://psasir.upm.edu.my/id/eprint/86874/
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spelling my.upm.eprints.868742021-10-11T07:36:10Z http://psasir.upm.edu.my/id/eprint/86874/ MYNursingHome: a fully-labelled image dataset for indoor object classification Ismail, Asmida Ahmad, Siti Anom Che Soh, Azura Hassan, Mohd Khair Harith, Hazreen Haizi 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. Elsevier 2020-10 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/86874/1/MYNursingHome.pdf Ismail, Asmida and Ahmad, Siti Anom and Che Soh, Azura and Hassan, Mohd Khair and Harith, Hazreen Haizi (2020) MYNursingHome: a fully-labelled image dataset for indoor object classification. Data in Brief, 32. art. no. 106268. pp. 1-6. ISSN 2352-3409 ncedirect.com/science/article/pii/S2352340920311628#:~:text=MyNursingHome%20is%20a%20fully%20labelled,%2C%20recognition%2C%20segmentation%20and%20detection. 10.1016/j.dib.2020.106268
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description 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.
format Article
author Ismail, Asmida
Ahmad, Siti Anom
Che Soh, Azura
Hassan, Mohd Khair
Harith, Hazreen Haizi
spellingShingle Ismail, Asmida
Ahmad, Siti Anom
Che Soh, Azura
Hassan, Mohd Khair
Harith, Hazreen Haizi
MYNursingHome: a fully-labelled image dataset for indoor object classification
author_facet Ismail, Asmida
Ahmad, Siti Anom
Che Soh, Azura
Hassan, Mohd Khair
Harith, Hazreen Haizi
author_sort Ismail, Asmida
title MYNursingHome: a fully-labelled image dataset for indoor object classification
title_short MYNursingHome: a fully-labelled image dataset for indoor object classification
title_full MYNursingHome: a fully-labelled image dataset for indoor object classification
title_fullStr MYNursingHome: a fully-labelled image dataset for indoor object classification
title_full_unstemmed MYNursingHome: a fully-labelled image dataset for indoor object classification
title_sort mynursinghome: a fully-labelled image dataset for indoor object classification
publisher Elsevier
publishDate 2020
url http://psasir.upm.edu.my/id/eprint/86874/1/MYNursingHome.pdf
http://psasir.upm.edu.my/id/eprint/86874/
_version_ 1715191567798501376
score 13.211869

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