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博士生导师

刘羽

2017-06-07


姓名

刘羽

职称

副教授

所属系

生物医学工程系

邮箱

yuliu@hfut.edu.cn

电话


个人简历

刘羽,副教授,博士生导师,科睿唯安(Clarivate)全球高被引科学家、爱思唯尔(Elsevier)中国高被引学者2007-2016年就读于中国科学技术大学信息科学技术学院,获工学学士学位(20116月)、工学博士学位(20166月),曾获第30届中科大郭沫若奖学金、中国科学院院长优秀奖。20167月进入合肥工业大学仪器科学与光电工程学院工作。目前主要从事图像处理、计算机视觉、机器学习相关方向的研究,具体包括图像融合、图像复原、医学图像分析、生理电信号处理等。近年来,作为项目负责人承担了国家自然科学基金面上项目/青年基金、安徽省自然科学基金、商汤青年科研基金、校优秀青年人才培育计划A项目等多项科研项目。近年来,在IJCVINFFUSIEEE TIPIEEE TCSVTIEEE TGRSIEEE TIMIEEE TCIIEEE JBHIIEEE SPLIEEE/CAA JAS(自动化学报(英文版))、中国图象图形学报等国内外知名学术期刊和会议上发表论文100余篇,其中第一/通讯作者论文50余篇。论文谷歌学术总计被引10000余次21篇论文单篇被引超过100次(14篇为第一/通讯作者),20篇论文入选ESI高被引论文(11篇为第一/通讯作者),3篇论文入选ESI热点论文(2篇为第一/通讯作者)。个人入选Clarivate全球高被引科学家(2023入选Elsevier中国高被引学者榜单(2020至今)、入选斯坦福大学“全球前2%顶尖科学家”榜单(2020至今)。获安徽省自然科学二等奖(20193/3)、IEEE仪器与测量汇刊IEEE Transactions on Instrumentation and Measurement年度最佳论文奖(2020,通讯作者)、国际知名期刊IET Image Processing年度最佳论文奖(2017,第一作者)、中国仪器仪表学会金国藩青年学子奖(2022)。担任Information Fusion(影响因子:18.6)、IEEE Signal Processing Letters(影响因子:3.9)、中国图象图形学报(CCF推荐中文科技期刊)等多个国内外知名期刊编委。担任中国图象图形学学会(CSIG)机器视觉专委会委员、医学图像计算青年研讨会(MICS)委员。担任IEEE TPAMIIEEE TIPIEEE TMIIEEE TMMIEEE TBMEIEEE TIMInformation FusionPattern RecognitionOptics Express30余个国际知名期刊审稿人。

研究领域

图像处理、计算机视觉、机器学习相关方向,主要包括图像融合、图像复原、医学图像分析、生理电信号处理等

开设课程

本科生:《数字图像处理》(2018至今)、《医学模式识别》(2017-2021

研究生:《医学图像分析》(2022至今)、《模式识别》(2017-2022

科研项目

1. 国家自然科学基金面上项目,62176081,项目负责人

2. 国家自然科学基金区域联合基金重点支持项目,U23A20294,合作单位负责人

3. 国家重点研发计划项目,2019YFA0706203,项目骨干、子课题负责人

4. 国家自然科学基金青年科学基金项目,61701160,项目负责人

5. 安徽省自然科学基金青年基金项目,1808085QF186,项目负责人 (结题评价“优”,比例10%

6. 商汤青年科研基金,W2018JSKF0481,项目负责人

7. 合肥工业大学优秀青年人才培育计划A项目,JZ2020HGPA0111,项目负责人(入选典型案例)

8. 合肥工业大学学术新人提升计划B项目,JZ2018HGTB0228,项目负责人

9. 合肥工业大学学术新人提升计划A项目,JZ2017HGTA0176,项目负责人(入选典型案例)

发表论文

主要第一/通讯作者论文(*表示通讯作者):

1. Yu Liu, Shuping Liu, Zengfu Wang, “A general framework for image fusion based on multi-scale transform and sparse representation,” Information Fusion, vol. 24, pp. 147-164, 2015. 引用次数:1100+. ESI热点论文、ESI高被引论文

2. 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. 引用次数:1000+.ESI高被引论文

3. Yu Liu, Xun Chen, Rabab K. Ward, Z. Jane Wang, “Image fusion with convolutional sparse representation,” IEEE Signal Processing Letters, vol. 23, no. 12, pp. 1882-1886, 2016. 引用次数:700+. ESI高被引论文

4. Yu Liu, Xun Chen, Zengfu Wang, Z. Jane Wang, Rabab K. Ward, Xuesong Wang, “Deep learning for pixel-level image fusion: Recent advances and future prospects,” Information Fusion, vol. 42, pp. 158-173, 2018. 引用次数:500+. 特邀综述、ESI高被引论文

5. 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. 引用次数:400+. 期刊年度最佳论文(1/500+)、ESI高被引论文

6. Yu Liu, Shuping Liu, Zengfu Wang, “Multi-focus image fusion with dense SIFT,” Information Fusion, vol. 23, pp. 139-155, 2015. 引用次数:400+.ESI高被引论文

7. Yu Liu, Zengfu Wang, “Simultaneous image fusion and denoising with adaptive sparse representation,” IET Image Processing, vol. 9, no. 5, pp. 347-357, 2015. 引用次数:300+. 期刊年度最佳论文(1/200+)、ESI高被引论文

8. Yu Liu, Xun Chen, Juan Cheng, Hu Peng, Zengfu Wang, “Infrared and visible image fusion with convolutional neural networks,” International Journal of Wavelets, Multiresolution and Information Processing, vol. 16, no. 3, p. 1850018, 2018. 引用次数:300+. ESI高被引论文

9. Yu Liu, Xun Chen, Rabab K. Ward, Z. Jane Wang, “Medical image fusion via convolutional sparsity based morphological component analysis,” IEEE Signal Processing Letters, vol. 26, no. 3, pp. 485-489, 2019. 引用次数:200+. ESI高被引论文

10. Yu Liu, Lei Wang, Juan Cheng, Chang Li, Xun Chen, “Multi-focus image fusion: A survey of the state of the art,” Information Fusion, vol. 64, pp. 71-91, 2020. 引用次数:100+. 特邀综述. ESI高被引论文

11. Zhiqin Zhu, Xianyu He, Guanqiu Qi, Yuanyuan Li, Baisen Cong, Yu Liu*, “Brain tumor segmentation based on the fusion of deep semantics and edge information in multimodal MRI,” Information Fusion, vol. 91, pp. 376-387, 2023. 引用次数:100+. ESI热点论文、ESI高被引论文

12. 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.

13. 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.

14. Yu Liu, Yi Wei, Chang Li, Juan Cheng, Rencheng Song, Xun Chen, “Bi-CapsNet: A Binary Capsule Network for EEG-based Emotion Recognition,” IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 3, pp. 1319-1330, 2023.

15. Yu Liu, Zhigang Yang, Juan Cheng, Xun Chen, “Multi-Exposure Image Fusion via Multi-scale and Context-aware Feature Learning,” IEEE Signal Processing Letters, vol. 30, pp. 100-104, 2023.

16. Yi Wei, Yu Liu*, Chang Li, Juan Cheng, Rencheng Song, Xun Chen, “TC-Net: A Transformer Capsule Network for EEG-based Emotion Recognition,” Computers in Biology and Medicine, vol. 152, p. 106463, 2023.

17. Yu Liu, Hao Zhao, Rencheng Song, Xudong Chen, Chang Li, Xun Chen, “SOM-Net: Unrolling the Subspace-based Optimization for Solving Full-wave Inverse Scattering Problems,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, p. 2007715, 2022.

18. Yu Liu, Yu Shi, Fuhao Mu, Juan Cheng, Chang Li, Xun Chen, “Multimodal MRI Volumetric Data Fusion with Convolutional Neural Networks,” IEEE Transactions on Instrumentation and Measurement, vol. 71, p. 4006015, 2022.

19. Yu Liu, Lei Wang, Huafeng Li, Xun Chen, “Multi-focus image fusion with deep residual learning and focus property detection,” Information Fusion, vol. 86-87, pp. 1-16, 2022.   

20. 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.

21. Yu Liu, Fuhao Mu, Yu Shi, Xun Chen, “SF-Net: A Multi-task Model for Brain Tumor Segmentation in Multimodal MRI via Image Fusion,” IEEE Signal Processing Letters, vol. 29, pp. 1799-1803, 2022.

22. Yu Liu, Lei Wang, Juan Cheng, Xun Chen, “Multiscale feature interactive network for multifocus image fusion,” IEEE Transactions on Instrumentation and Measurement, vol. 70, p. 5019316, 2021.

23. Huafeng Li, Yueliang Cen, Yu Liu*, Xun Chen, Zhengtao Yu, “Different input resolutions and arbitrary output resolution: A meta learning-based deep framework for infrared and visible image fusion,” IEEE Transactions on Image Processing, vol. 30, pp. 4070-4083, 2021.

24. Wei Tang, Yu Liu*, Juan Cheng, Chang Li, Xun Chen, “Green fluorescent protein and phase contrast image fusion via detail preserving cross network,” IEEE Transactions on Computational Imaging, vol. 7, pp. 584-597, 2021.

25. Rencheng Song, Qiao Zhou, Yu Liu*, Chang Li, Xun Chen, “A convolutional sparsity regularization for solving inverse scattering problems,” IEEE Antennas and Wireless Propagation Letters, vol. 20, no. 12, pp. 2285-2289, 2021.

26. Yu Liu, Yufeng Ding, Chang Li, Juan Cheng, Rencheng Song, Feng Wan, Xun Chen, “Multi-channel EEG-based emotion recognition via a multi-level features guided capsule network,” Computers in Biology and Medicine, vol. 123, p. 103927, 2020. 引用次数:100+

27. Yu Liu, Chao Zhang, Chang Li, Juan Cheng, Yadong Zhang, Huiqin Xu, Tao Song, Liang Zhao, Xun Chen, “A practical PET/CT data visualization method with dual-threshold PET colorization and image fusion,” Computers in Biology and Medicine, vol. 126, p. 104050, 2020.

28. Wei Tang, Yu Liu*, Juan Cheng, Chang Li, Hu Peng, Xun Chen, “A phase congruency-based green fluorescent protein and phase contrast image fusion method in nonsubsampled shearlet transform domain,” Microscopy Research and Technique, vol. 83, no. 10, pp. 1225-1234, 2020. 期刊年度最佳论文(15/200+

29. Yu Liu, Chao Zhang, Juan Cheng, Xun Chen, Z. Jane Wang, “A multi-scale data fusion framework for bone age assessment with convolutional neural networks,” Computers in Biology and Medicine, vol. 108, pp. 161-173, 2019.

30. Yu Liu, Zengfu Wang, “Dense SIFT for ghost-free multi-exposure fusion,” Journal of Visual Communication and Image Representation, vol. 31, pp. 208-224, 2015. 引用次数:100+


谷歌学术主页:https://scholar.google.com/citations?user=r4cmlNgAAAAJ&hl=zh-CN

专著教材

申请专利

1. 刘羽,张超,陈勋,等,基于非下采样轮廓波变换和卷积神经网络的骨龄评估方法,中国发明专利,专利授权号:ZL201810965998.7

2. 刘羽,张超,宋涛,图像处理方法及装置、电子设备和存储介质,中国发明专利,专利授权号:ZL201911038127.1

3. 刘羽,王磊,李畅,等,一种基于多尺度特征交互网络的多聚焦图像融合方法,中国发明专利,专利授权号:ZL202110997261.5

4. 汪增福, 刘羽,一种实时的多模态医学图像融合方法,中国发明专利,专利授权号:ZL201410427772.3

5. 李畅,刘羽,成娟,等,一种基于逐波段广义双线性模型的高光谱图像的解混方法,中国发明专利,专利授权号:ZL201811097454.X

6. 成娟,魏馥琳,刘羽,等,一种中国普乐手语编码的手势动作识别方法,中国发明专利,专利授权号:ZL201910339115.6

7. 成娟,张楚雅,刘羽,等,一种基于级联U-Net网络的多模态图像分割方法,中国发明专利,专利授权号:ZL202110075561.8

8. 宋仁成,黄优优,刘羽,等,一种基于感知生成对抗网络的电磁逆散射成像方法,中国发明专利,专利授权号:ZL202010870574.X

9. 李畅,王彬,刘羽,等,一种基于多任务胶囊的脑电情绪识别方法,中国发明专利,专利授权号:ZL202111060732.6

10. 李畅,侯艺萌,成娟,刘羽,等,一种标签噪声下的脑电信号情绪识别方法,中国发明专利,专利授权号:ZL202110042672.9

获奖成果

1. Clarivate全球高被引学科学家(2023

2. Elsevier中国高被引学者(202020212022

3. 全球前2%顶尖科学家(2020202120222023

4. 安徽省自然科学二等奖(20193/3

5. 国际期刊IEEE Transactions on Instrumentation and Measurement年度最佳论文奖(2020,通讯作者)

6. 国际期刊IET Image Processing年度最佳论文奖(2017,第一作者)

7. 中国仪器仪表学会金国藩青年学子奖(2022

8. 中国生物医学工程学会青年论文竞赛二等奖(2017

9. 中国科学院院长优秀奖(2015

10. 中国科大郭沫若奖学金(2010


指导研究生获奖情况:

2017级:张超,硕士生国家奖学金;

2018级:唐伟,硕士生国家奖学金、合肥工业大学优秀毕业生、安徽省优秀毕业生;

2019级:王磊,硕士生国家奖学金、合肥工业大学优秀毕业生;

2020级:石雨,硕士生国家奖学金、合肥工业大学优秀毕业生、安徽省优秀毕业生;

2021级:李海航、杨智刚,硕士生国家奖学金