Badawy, M.; Rashed, A.; Bamaqa, A.; Sayed, H.A.; Elagamy, R.; Almaliki, M.; Farrag, T.A.; Elhosseini, M.A.
From Sensors to Insights: Interpretable Audio-Based Machine Learning for Real-Time Vehicle Fault and Emergency Sound Classification. Machines 2025, 13, 888.
https://doi.org/10.3390/machines13100888
AMA Style
Badawy M, Rashed A, Bamaqa A, Sayed HA, Elagamy R, Almaliki M, Farrag TA, Elhosseini MA.
From Sensors to Insights: Interpretable Audio-Based Machine Learning for Real-Time Vehicle Fault and Emergency Sound Classification. Machines. 2025; 13(10):888.
https://doi.org/10.3390/machines13100888
Chicago/Turabian Style
Badawy, Mahmoud, Amr Rashed, Amna Bamaqa, Hanaa A. Sayed, Rasha Elagamy, Malik Almaliki, Tamer Ahmed Farrag, and Mostafa A. Elhosseini.
2025. "From Sensors to Insights: Interpretable Audio-Based Machine Learning for Real-Time Vehicle Fault and Emergency Sound Classification" Machines 13, no. 10: 888.
https://doi.org/10.3390/machines13100888
APA Style
Badawy, M., Rashed, A., Bamaqa, A., Sayed, H. A., Elagamy, R., Almaliki, M., Farrag, T. A., & Elhosseini, M. A.
(2025). From Sensors to Insights: Interpretable Audio-Based Machine Learning for Real-Time Vehicle Fault and Emergency Sound Classification. Machines, 13(10), 888.
https://doi.org/10.3390/machines13100888
