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副教授

副教授

刘羽*

2021-09-07 浏览次数:541

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,博士,副教授,硕士生导师,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、图像超分辨、医学图像分析等。近年来,作为项目负责人承担了国家自然科学基金、安徽省自然科学基金、校优秀青年人才培育计划A项目等多项科研项目。在Information FusionIEEE TIPIEEE TCIIEEE TIMIEEE SPLCBMIET IP、中国图象图形学报、ICIPICIFMMSP等国内外知名学术期刊和会议上发表论文50余篇,其中以第一/通讯作者身份发表论文30余篇。论文总计被引4000余次(Google Scholar),11篇论文被引超过100次(其中8篇第一作者、1篇通讯作者、2篇第二作者),9篇论文入选ESI 高被引论文(其中6篇第一作者、1篇通讯作者、2篇第二作者),2篇论文入选ESI热点论文(其中1篇第一作者、1篇第二作者)。入选Elsevier 2020中国高被引学者榜单,获国际期刊IEEE TIM年度最佳论文奖(2020,通讯作者)、国际期刊IET IP年度最佳论文奖(2017,第一作者)、安徽省自然科学二等奖(20193/3)。担任Information Fusion3个国际期刊编委。担任IEEE TPAMIIEEE TIPIEEE TMMIEEE TBMEIEEE TIMIEEE SPLInformation FusionPattern RecognitionSignal ProcessingOptics Express30余个国际期刊审稿人。

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、图像超分辨、医学图像分析、生理电信号处理与分析等

开设课程

本科生:《数字图像处理》、《医学模式识别》

研究生:《模式识别》

科研项目

1. 国家自然科学基金面上项目,62176081,项目负责人

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

3. 国家自然科学基金青年科学基金项目,61701160,项目负责人

4. 安徽省自然科学基金青年基金项目,1808085QF186,项目负责人

5. 商汤青年科研基金,W2018JSKF0481,项目负责人

6. 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

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

8. 合肥工业大学学术新人提升计划A项目,JZ2017HGTA0176,项目负责人

发表论文

主要学术论文(*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. Google Scholar引用次数:700+. 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. Google Scholar引用次数:500+. 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. Google Scholar引用次数:350+. ESI高被引论文

4. 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引用次数:180+. IEEE TIM年度最佳论文、ESI高被引论文

5. Yu Liu, Shuping Liu, Zengfu Wang, “Multi-focus image fusion with dense SIFT,” Information Fusion, vol. 23, pp. 139-155, 2015. Google Scholar引用次数:290+. ESI高被引论文

6. 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. Google Scholar引用次数:300+.特邀综述、ESI高被引论文

7. 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. Google Scholar引用次数:80+. ESI高被引论文

8. Yu Liu, Zengfu Wang, “Simultaneous image fusion and denoising with adaptive sparse representation,” IET Image Processing, vol. 9, no. 5, pp. 347-357, 2015. Google Scholar引用次数:190+. IET IP年度最佳论文

9. 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.

10. 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.

11. Yu Liu, Xun Chen, Aiping Liu, Rabab. K. Ward, Z. Jane Wang, “Recent advances in sparse representation based medical image fusion,” IEEE Instrumentation & Measurement Magazine, vol. 24, no. 2, pp. 45-53, 2021. 特邀综述

12. 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, early access, 2021.

13. 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.

14. 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. 特邀综述

15. 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.

16. Yu Zhang, Yu Liu, Peng Sun, Han Yan, Xiaolin Zhao, Li Zhang, “IFCNN: A general image fusion framework based on convolutional neural network,” Information Fusion, vol. 54, pp. 99-118, 2020. Google Scholar引用次数:100+. ESI高被引论文

17. 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.

18. Lei Ma, Yu Liu, Xueliang Zhang, Yuanxin Ye, Gaofei Yin, Brian Alan Johoson, “Deep learning in remote sensing applications: A meta-analysis and review,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 152, pp. 166-177, 2019. Google Scholar引用次数:500+. ESI热点论文、ESI高被引论文

19. Dingyi Li, Yu Liu, Zengfu Wang, “Video super-resolution using non-simultaneous fully recurrent convolutional network,” IEEE Transactions on Image Processing, vol. 28, no. 3, pp. 1342-1355, 2019.

20. 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. Google Scholar引用次数:120+. Most Cited Article of this Journal

21. Yu Liu, Xun Chen, Juan Cheng, Hu Peng, “A medical image fusion method based on convolutional neural networks,” 20th International Conference on Information Fusion, Xi’an, China, July 10-13, 2017, pp. 1070-1076. Google Scholar引用次数:140+.

22. Yu Liu, Baocai Yin, Jun Yu, Zengfu Wang, “Image classification based on convolutional neural networks with cross-level strategy,” Multimedia Tools and Applications, vol. 76, no. 8, pp. 11065-11079, 2017.

23. 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.

24. Yu Liu, Shuping Liu, Yang Cao, Zengfu Wang, “A practical algorithm for automatic chessboard corner detection,” 21th IEEE International Conference on Image Processing (ICIP), Paris, France, Oct. 27-30, 2014, pp. 3394-3398.

25. 刘羽, 汪增福. 结合小波变换和自适应分块的多聚焦图像快速融合, 中国图象图形学报, vol. 18, no. 11, pp. 1435-1444, 2013.

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. 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

2. 李畅,刘羽,成娟,宋仁成,彭虎. 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

3. 成娟,魏馥琳,刘羽,陈勋,李畅,宋仁成,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

4. 宋仁成,张森乐,陈勋,成娟,李畅,刘爱萍,刘羽,一种基于卷积神经网络的非接触式心率测量方法,中国发明专利,专利授权号:ZL201910304963.3

5. 刘羽,张超,陈勋,成娟,李畅,宋仁成,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,专利申请号:201810965998.7

6. 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,专利申请号:201911038127.1

7. 成娟,张楚雅,刘羽,李畅,宋仁成,陈勋,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,专利申请号:202110075561.8

8. 刘羽,朱文瑜,成娟,李畅,宋仁成,陈勋,一种基于卷积神经网络的多模态图像超分辨方法,中国发明专利,专利申请号:202110870612.6

9. 刘羽,危仪,李畅,成娟,宋仁成,陈勋,一种基于二值胶囊网络的脑电情绪识别方法,中国发明专利,专利申请号:202110871951.6

10. 刘羽、王磊、成娟、李畅、宋仁成、陈勋,一种基于多尺度特征交互网络的多聚焦图像融合方法。专利申请号:202110997261.5


获奖成果

1. Elsevier 2020中国高被引学者(入选学科:生物医学工程)

2. 安徽省自然科学二等奖(20193/3

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

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