Conventional Machine Learning and Feature Engineering for Vocal Fold Precancerous Lesions Detection Using Acoustic Features
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s00034-023-02551-8.pdf
Reference73 articles.
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2. A.B. Aicha, Contribution of data augmentation for the prenventive detection of vocal fold precancerous lesions. Proc. Comput. Sci. 159, 212–220 (2019)
3. A.B. Aicha, Conventional machine learning techniques with features engineering for preventive larynx cancer detection, in 2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), IEEE, (2020), pp. 1–5
4. A.B. Aicha, K. Ezzine, Cancer larynx detection using glottal flow parameters and statistical tools, in International Symposium on Signal, Image, Video and Communications (ISIVC), IEEE, (2016), pp. 65–70
5. A. Al-Nasheri, M. Ghulam, M. Alsulaiman, A. Zulfiqar, Investigation of voice pathology detection and classification on different frequency regions using correlation functions. J. Voice 31, 3–15 (2017)
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