Unsupervised Learning for Understanding Diversity: Applying Feature Engineering and Cluster Analysis to Deaf and Hard of Hearing Data
- Title
- Unsupervised Learning for Understanding Diversity: Applying Feature Engineering and Cluster Analysis to Deaf and Hard of Hearing Data
- Description
- 2024 International Conference on Control, Automation and Diagnosis, ICCAD 2024
- Creator
- Poly A.; Banu P.K.N.; Azar A.T.; Kamal N.A.
- Source
- <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197931398&doi=10.1109%2fICCAD60883.2024.10553733&partnerID=40&md5=9e8af81734149ae18d5f0ecb09916c4d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197931398&doi=10.1109%2fICCAD60883.2024.10553733&partnerID=40&md5=9e8af81734149ae18d5f0ecb09916c4d</a>
- Date
- 2024-01-01
Collection
Citation
Poly A.; Banu P.K.N.; Azar A.T.; Kamal N.A., “Unsupervised Learning for Understanding Diversity: Applying Feature Engineering and Cluster Analysis to Deaf and Hard of Hearing Data,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 10, 2025, https://archives.christuniversity.in/items/show/9722.