Yuxuan Zhang
Doktorand|Doctoral Student
- Tjänstetitel: Doktorand
- Akademisk titel: Doktorand
- Telefon arbete: +46 (0)10-1428004
- E-postadress: yuxuan.zhang@miun.se
- Rumsnummer: L331
- Ort: Sundsvall
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- Anställd inom ämnet:
- Elektronik
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- Forskningscentra:
- Sensible Things that Communicate, STC
Bakgrund
Yuxuan Zhang completed his Master's Degree in Embedded Systems Engineering from the University of Leeds, Leeds, UK, in 2019. He joined Mid Sweden University in 2021 as a Doctoral Student.
Forskningsområden
Yuxuan's current research focuses on the performance and optimization of deep learning/machine learning on low-power MCUs, with a particular focus on structural health monitoring applications.
Övrigt
ORCID: 0000-0002-8617-0435
Personal Website: Yuxuan Zhang (张宇轩)
Publikationer
Artiklar i tidskrifter
Konferensbidrag
Licentiatavhandlingar, sammanläggningar
Artiklar i tidskrifter
Zhang, Y. , Pullin, R. , Oelmann, B. & Bader, S. (2025). On-Device Fault Diagnosis with Augmented Acoustic Emission Data : A Case Study on Carbon Fiber Panels. IEEE Transactions on Instrumentation and Measurement, vol. 74, ss. 1-12.
Xie, Y. , Nie, Y. , Lundgren, J. , Yang, M. , Zhang, Y. & Chen, Z. (2024). Cervical Spondylosis Diagnosis Based on Convolutional Neural Network with X-ray Images. Sensors, vol. 24: 11
Huang, C. , Sun, X. & Zhang, Y. (2024). Tiny-Machine-Learning-Based Supply Canal Surface Condition Monitoring. Sensors, vol. 24: 13
Zhang, Y. , Adin, V. , Bader, S. & Oelmann, B. (2023). Leveraging Acoustic Emission and Machine Learning for Concrete Materials Damage Classification on Embedded Devices. IEEE Transactions on Instrumentation and Measurement, vol. 72
Konferensbidrag
Martinez Rau, L. S. , Zhang, Y. , Nguyen Phuong Vu, Q. , Oelmann, B. & Bader, S. (2025). An On-Device Hybrid Machine Learning Approach for Anomaly Detection in Conveyor Belt Operations. I 2025 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).
Nguyen Phuong Vu, Q. , Martinez Rau, L. S. , Zhang, Y. , Tran, N. D. , Oelmann, B. , Magno, M. & Bader, S. (2025). Efficient Continual Learning in Keyword Spotting using Binary Neural Networks. I 2025 IEEE Sensors Applications Symposium (SAS).. S. 1--6.
Li, W. , Wu, X. , Hu, X. , Zhang, Y. , Bader, S. & Huang, Y. (2025). LD-RPMNet: Near-Sensor Diagnosis for Railway Point Machines. I 2025 IEEE Sensors Applications Symposium (SAS).. S. 1--6.
Wang, X. , Li, H. , Liu, Z. , Zhang, J. , Zhang, Y. & Bader, S. (2025). Long short-term memory-optimized time difference mapping for enhanced acoustic emission source localization in composite materials. I 2025 IEEE Sensors Applications Symposium (SAS).. S. 1--6.
Zhang, Y. , Xu, Y. , Martinez Rau, L. S. , Nguyen Phuong Vu, Q. , Oelmann, B. & Bader, S. (2025). On-Device Crack Segmentation for Edge Structural Health Monitoring. I 2025 IEEE Sensors Applications Symposium (SAS).. S. 1--6.
Zhang, Y. , Martinez Rau, L. S. , Nguyen Phuong Vu, Q. , Oelmann, B. & Bader, S. (2025). Survey of Quantization Techniques for On-Device Vision-based Crack Detection. I 2025 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).
Muthumala, U. , Zhang, Y. , Martinez Rau, L. & Bader, S. (2024). Comparison of Tiny Machine Learning Techniques for Embedded Acoustic Emission Analysis. I 2024 IEEE 10th World Forum on Internet of Things (WF-IoT).
Zhang, Y. , Martinez Rau, L. , Oelmann, B. & Bader, S. (2024). Enabling Autonomous Structural Inspections with Tiny Machine Learning on UAVs. I 2024 IEEE Sensors Applications Symposium, SAS 2024 - Proceedings.
Martinez Rau, L. , Zhang, Y. , Oelmann, B. & Bader, S. (2024). TinyML Anomaly Detection for Industrial Machines with Periodic Duty Cycles. I 2024 IEEE Sensors Applications Symposium, SAS 2024 - Proceedings.
Adin, V. , Zhang, Y. , Oelmann, B. & Bader, S. (2023). Tiny Machine Learning for Damage Classification in Concrete Using Acoustic Emission Signals. I 2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).
Adin, V. , Zhang, Y. , Ando, B. , Oelmann, B. & Bader, S. (2023). Tiny Machine Learning for Real-Time Postural Stability Analysis. I 2023 IEEE Sensors Applications Symposium (SAS).
Zhang, Y. , Bader, S. & Oelmann, B. (2022). A Lightweight Convolutional Neural Network Model for Concrete Damage Classification using Acoustic Emissions. I 2022 IEEE Sensors Applications Symposium, SAS 2022 - Proceedings.
Licentiatavhandlingar
Zhang, Y. (2024). Tiny Machine Learning for Structural Health Monitoring with Acoustic Emissions. Lic.-avh. (Sammanläggning) Sundsvall : Mid Sweden University, 2024 (Mid Sweden University licentiate thesis : 204)
Manuskript
Zhang, Y. , Arne, N. , Martinez Rau, L. , Nguyen Phuong Vu, Q. , Lu, Y. , Oelmann, B. & Bader, S. TinyML Pipeline for Efficient Crack Classification in UAV-based Structural Health Inspections.