Facial Detection for Neonatal Infant Pain Using Facial Geometry Features and LBP-Reference-Cited by-同舟云学术

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Facial Detection for Neonatal Infant Pain Using Facial Geometry Features and LBP

Published:2022 Issue: Volume: Page:509-518
ISSN:2367-3370
Container-title:Proceedings of the Third International Conference on Trends in Computational and Cognitive Engineering
language:
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Author:

Ritu Jarin Tasnim,Shakil Md. Shahadat Hossen,Hasan Md. Nahian Imtiaz,Al Mamun Shamim^ORCID,Kaiser M. Shamim^ORCID,Mahmud Mufti^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-7597-3_42

Reference21 articles.

1. Al Mamun, S., Daud, M.E., Mahmud, M., Kaiser, M.S., Rossi, A.L.D.: ALO: AI for least observed people. In: International Conference on Applied Intelligence and Informatics, pp. 306–317. Springer (2021)

2. Rahman, M.M., Al Mamun, S., Kaiser, M.S., Islam, M.S., Rahman, M.A.: Cascade classification of face liveliness detection using heart beat measurement. In: Proceedings of International Conference on Trends in Computational and Cognitive Engineering, pp. 581–590. Springer (2021)

3. Mahmud, M., Kaiser, M.S., Rahman, M.M., Rahman, M.A., Shabut, A., Al-Mamun, S., Hussain, A.: A brain-inspired trust management model to assure security in a cloud based IoT framework for neuroscience applications. Cogn. Comput. 10(5), 864–873 (2018)

4. Noor, M.B.T., Zenia, N.Z., Kaiser, M.S., Al Mamun, S., Mahmud, M.: Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia. Brain Inform. 7(1), 1–21 (2020)

5. Al Mamun, S., Lam, A., Kobayashi, Y., Kuno, Y.: Single laser bidirectional sensing for robotic wheelchair step detection and measurement. In: International Conference on Intelligent Computing, pp. 37–47. Springer (2017)

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