Ullah, S.; Ullah, N.; Siddique, M.F.; Ahmad, Z.; Kim, J.-M.
Spatio-Temporal Feature Extraction for Pipeline Leak Detection in Smart Cities Using Acoustic Emission Signals: A One-Dimensional Hybrid Convolutional Neural Network–Long Short-Term Memory Approach. Appl. Sci. 2024, 14, 10339.
https://doi.org/10.3390/app142210339
AMA Style
Ullah S, Ullah N, Siddique MF, Ahmad Z, Kim J-M.
Spatio-Temporal Feature Extraction for Pipeline Leak Detection in Smart Cities Using Acoustic Emission Signals: A One-Dimensional Hybrid Convolutional Neural Network–Long Short-Term Memory Approach. Applied Sciences. 2024; 14(22):10339.
https://doi.org/10.3390/app142210339
Chicago/Turabian Style
Ullah, Saif, Niamat Ullah, Muhammad Farooq Siddique, Zahoor Ahmad, and Jong-Myon Kim.
2024. "Spatio-Temporal Feature Extraction for Pipeline Leak Detection in Smart Cities Using Acoustic Emission Signals: A One-Dimensional Hybrid Convolutional Neural Network–Long Short-Term Memory Approach" Applied Sciences 14, no. 22: 10339.
https://doi.org/10.3390/app142210339
APA Style
Ullah, S., Ullah, N., Siddique, M. F., Ahmad, Z., & Kim, J.-M.
(2024). Spatio-Temporal Feature Extraction for Pipeline Leak Detection in Smart Cities Using Acoustic Emission Signals: A One-Dimensional Hybrid Convolutional Neural Network–Long Short-Term Memory Approach. Applied Sciences, 14(22), 10339.
https://doi.org/10.3390/app142210339
