Thanh Tran
- Ansvarsområde: Apply deep learning in digital signal and image processing, industrial sound measurements, and machine fault diagnosis.
- E-postadress: thanh.tran@miun.se
- Rumsnummer: Ej Angivet
- Ort: Sundsvall
- Datavetenskap
- Ljudproduktion
-
Anställd inom ämnet:
Bakgrund
Thanh Tran earned her M.S. degree from the Department of IT Convergence and Application Engineering at Pukyong National University, Busan, South Korea, in 2019. She later obtained a Ph.D. from the Department of Computer and Electrical Engineering (DET) at the STC Research Centre, Mid Sweden University in 2023. Tran's research primarily focuses on leveraging artificial intelligence in digital signal and image processing, with special emphasis on industrial sound measurements and machine fault diagnosis. Recognized for her expertise, she has been invited to review papers for various prestigious conferences and journals, including the IEEE World Congress on Computational Intelligence 2022, IJCNN 2023, IJCNN 2024, Elsevier Pattern Recognition Letters, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Elsevier's Innovation and Research in BioMedical Engineering (IRBM), the Jordanian Journal of Computers and Information Technology, Springer's Soft Computing, Wiley's International Journal for Numerical Methods in Biomedical Engineering, and IEEE Access.
Forskning
11 peer-reviewed publications in journals and conferences. The publications have been cited 315 times, of which the most cited publication accounts for 123 citations. The author has an h-index of 7 (Google Scholar).
Extra kontaktinformation
Publikationer
Artiklar i tidskrifter
Doktorsavhandlingar, sammanläggningar
Konferensbidrag
Licentiatavhandlingar, sammanläggningar
Artiklar i tidskrifter
Tran, T. , Truong Pham, N.
&
Lundgren, J. (2022). A deep learning approach for detecting drill bit failures from a small sound dataset. Scientific Reports, vol. 12
Tran, T.
&
Lundgren, J. (2020). Drill Fault Diagnosis Based on the Scalogram and Mel Spectrogram of Sound Signals Using Artificial Intelligence. IEEE Access, vol. 8, ss. 203655-203666.
Doktorsavhandlingar
Tran, T. (2023). Enhancing Machine Failure Detection with Artificial Intelligence and sound Analysis. Diss. (Sammanläggning) Sundsvall : Mid Sweden University, 2023 (Mid Sweden University doctoral thesis : 395)
Konferensbidrag
Tran, T. , Bader, S.
&
Lundgren, J. (2023). Denoising Induction Motor Sounds Using an Autoencoder.
I
2023 IEEE Sensors Applications Symposium (SAS).. S. 01--06.
Tran, T. , Bader, S.
&
Lundgren, J. (2022). An artificial neural network-based system for detecting machine failures using a tiny sound dataset : A case study.
I
Proceedings - 2022 IEEE International Symposium on Multimedia, ISM 2022.. S. 163--168.
Tran, T. , Huy, K. B. , Pham, N. T. , Carratù, M. , Liguori, C.
&
Thim, J. (2021). Separate Sound into STFT Frames to Eliminate Sound Noise Frames in Sound Classification.
Paper presented at the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2021), Orlando, USA, [DIGITAL], December 5-7, 2021.
Licentiatavhandlingar
Tran, T. (2021). Drill Failure Detection based on Sound using Artificial Intelligence. Lic.-avh. (Sammanläggning) Sundsvall, Sweden : Mid Sweden University, 2021 (Mid Sweden University licentiate thesis : 188)