Real-Time Recognition of NZ Sign Language Alphabets by Optimal Use of Machine Learning

Mubashir Ali, Seyed Ebrahim Hosseini, Shahbaz Pervez, Muneer Ahmad

Open source

DOI: 10.3390/bioengineering12101068
Published: 2025-09-30
Container: Bioengineering
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/bioengineering12101068,
  title = {Real-Time Recognition of NZ Sign Language Alphabets by Optimal Use of Machine Learning},
  author = {Mubashir Ali and Seyed Ebrahim Hosseini and Shahbaz Pervez and Muneer Ahmad},
  year = {2025},
  journal = {Bioengineering},
  doi = {10.3390/bioengineering12101068},
  url = {https://doi.org/10.3390/bioengineering12101068}
}

RIS

TY  - JOUR
TI  - Real-Time Recognition of NZ Sign Language Alphabets by Optimal Use of Machine Learning
AU  - Mubashir Ali
AU  - Seyed Ebrahim Hosseini
AU  - Shahbaz Pervez
AU  - Muneer Ahmad
PY  - 2025
JO  - Bioengineering
DO  - 10.3390/bioengineering12101068
UR  - https://doi.org/10.3390/bioengineering12101068
ER  -

APA

Ali, M., Hosseini, S. E., Pervez, S., & Ahmad, M. (2025). Real-Time Recognition of NZ Sign Language Alphabets by Optimal Use of Machine Learning. Bioengineering. https://doi.org/10.3390/bioengineering12101068

Source records

crossref · retrieved 2026-09-25T03:14:36.960Z