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Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: An Evaluation Cover

Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: An Evaluation

Journal of Automation, Mobile Robotics and Intelligent Systems
Volume 18 (2024): Issue 3 (September 2024)
By: Michał Kassjański,  Marcin Kulawiak,  Tomasz Przewoźny,  Dmitry Tretiakow,  Jagoda Kuryłowicz,  Andrzej Molisz,  Krzysztof Koźmiński,  Aleksandra Kwaśniewska,  Paulina Mierzwińska‑Dolny and  Miłosz Grono  
Open Access
|Sep 2024

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DOI: https://doi.org/10.14313/jamris/3-2024/19 | Journal eISSN: 2080-2145 | Journal ISSN: 1897-8649
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Language: English
Page range: 28 - 38
Submitted on: Dec 9, 2023
Accepted on: Mar 26, 2024
Published on: Sep 12, 2024
Published by: Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
classification,
hearing loss types,
pure-tone audiometry,
RNN,
LSTM,
evaluation
Related subjects:
Computer sciences,
Artificial intelligence,
Engineering,
Electrical engineering,
Control engineering, metrology and testing,
Mechanical engineering,
Fundamentals of mechanical engineering

© 2024 Michał Kassjański, Marcin Kulawiak, Tomasz Przewoźny, Dmitry Tretiakow, Jagoda Kuryłowicz, Andrzej Molisz, Krzysztof Koźmiński, Aleksandra Kwaśniewska, Paulina Mierzwińska‑Dolny, Miłosz Grono, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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