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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/86874/ http://psasir.upm.edu.my/id/eprint/86874/1/MYNursingHome.pdf |
| _version_ | 1848860310058827776 |
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| author | Ismail, Asmida Ahmad, Siti Anom Che Soh, Azura Hassan, Mohd Khair Harith, Hazreen Haizi |
| author_facet | Ismail, Asmida Ahmad, Siti Anom Che Soh, Azura Hassan, Mohd Khair Harith, Hazreen Haizi |
| author_sort | Ismail, Asmida |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T12:43:12Z |
| format | Article |
| id | upm-86874 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:43:12Z |
| publishDate | 2020 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| 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 |
| title | 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_short | MYNursingHome: a fully-labelled image dataset for indoor object classification |
| title_sort | mynursinghome: a fully-labelled image dataset for indoor object classification |
| url | http://psasir.upm.edu.my/id/eprint/86874/ http://psasir.upm.edu.my/id/eprint/86874/ http://psasir.upm.edu.my/id/eprint/86874/ http://psasir.upm.edu.my/id/eprint/86874/1/MYNursingHome.pdf |