Yu Liu

Associate Professor

Department of Biomedical Engineering

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Mail: Department of Biomedical Engineering

• 01, 2019 - Now: Associate Professor, Dept. of Biomedical Engineering, Hefei University of Technology, PR China (Ph. D. Supervisor since 2022)

• 07, 2016 - 12, 2018: Lecturer, Dept. of Biomedical Engineering, Hefei University of Technology, PR China (Master Supervisor since 2017)

• 09, 2011 - 06, 2016: Ph. D. Candidate, Dept. of Automation, University of Science and Technology of China, PR China (Recipient of 2015 President Outstanding Scholarship by Chinese Academy of Sciences)

• 09, 2007 - 06, 2016: Undergraduate Student, Dept. of Automation, University of Science and Technology of China, PR China (Recipient of the 30th GUO Moruo Scholarship, the Highest Award for Undergraduate Students at USTC)

Teaching

Undergraduate courses: Digital Image Processing

Postgraduate courses: Medical Image Analysis

Research

Dr. Yu Liu’s research interests include image processing, computer vision and machine learning. In particular, his current research is mainly focused on image fusion, image super-resolution, medical image segmentation, EEG emotion recognition, etc. He has published over 100 scientific articles in prestigious journals (e.g., IJCV, INFFUS, IEEE TIP/TCSVT/TGRS/TIM/TCI/JBHI/SPL) and conferences, including 20 ESI Highly Cited Papers. His publications have totally received over 10000 citations (Google Scholar: https://scholar.google.com/citations?user=r4cmlNgAAAAJ&hl=en). He is serving as an Editorial Board Member for Information Fusion, and an Associate Editor for IEEE Signal Processing Letters. He was a recipient of the IEEE Instrumentation and Measurement Society Andi Chi Best Paper Award in 2020 and the IET Image Processing Premium (Best Paper) Award in 2017. He is identified as an Elsevier Highly Cited Chinese Researcher (2020, 2021 and 2022).

Selected Papers/Patentsand Honors

1. Yu Liu, Xun Chen, Hu Peng, Zengfu Wang, “Multi-focus image fusion with a deep convolutional neural network,” Information Fusion, vol. 36, pp. 191-207, 2017. Google Scholar Citations: 1000+.  ESI Highly Cited Paper

2. Ming Yin, Xiaoning Liu, Yu Liu*, Xun Chen, “Medical image fusion with parameter-adaptive pulse coupled neural network in nonsubsampled shearlet transform domain,” IEEE Transactions on Instrumentation and Measurement, vol. 68, no. 1, pp. 49-64, 2019. Google Scholar Citations: 400+. IEEE TIM Best Paper Award. ESI Highly Cited Paper

3. Yu Liu, Yu Shi, Fuhao Mu, Juan Cheng, Xun Chen, “Glioma segmentation-oriented multi-modal MR image fusion with adversarial learning,” IEEE/CAA Journal of Automatica Sinica, vol. 9, no. 8, pp. 1528-1531, 2022.

4. Yu Liu, Haihang Li, Juan Cheng, Xun Chen, “MSCAF-Net: A general framework for camouflaged object detection via learning multi-scale context-aware features,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 33, no. 9, pp. 4934-4947, 2023.

5. Huafeng Li, Junyu Liu, Yafei Zhang, Yu Liu*, “A deep learning framework for infrared and visible image fusion without strict registration,” International Journal of Computer Vision, in press, 2023.