Machine learning classification method for wheelchair detection using bag-of-visual-words technique
The proposed method achieved an accuracy of 98.85%, demonstrating its effectiveness in identifying wheelchairs in images. These findings highlight the potential of object detection techniques in recognizing mobility aids, contributing to improved accessibility and safety in rehabilitation and assistive technology applications.
Authors
- Herman Khalid Omer
- Mosleh M. Abualhaj (ORCID: https://orcid.org/0000-0002-7465-8038)
- Ahmad Sami Al‐Shamayleh (ORCID: https://orcid.org/0000-0002-7222-2433)
- Hamid A. Jalab (ORCID: https://orcid.org/0000-0002-4823-6851)
- Qusai Y. Shambour (ORCID: https://orcid.org/0000-0002-3026-845X)
Institutions
- Al-Ahliyya Amman University (JO)
- Thi Qar University (IQ)
- Duhok Polytechnic University (IQ)
- Al-Ayen Iraqi University (IQ)
- Software (Spain) (ES)
Publication Details
- Journal
- Disability and Rehabilitation Assistive Technology
- Published
- 2025-03-11
- DOI
- https://doi.org/10.1080/17483107.2025.2476105
- Citations
- 4
- Primary Topic
- Gaze Tracking and Assistive Technology
- Type
- article
- Field-Weighted Citation Impact
- 7.74