檢視王瑜的原始碼

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|<center>''' 王瑜  '''<br><img src=" https://ai.btbu.edu.cn/images/2021-05/858d5fe5a45a4be08d62af31bce85282.jpg " width="180"></center><small>[https://ai.btbu.edu.cn/szdw/zc/js/81e6bd89b9034b24851946c58a1385e9.htm  北京工商大学]

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'''王瑜'''，女，北京工商大学教授。

==人物简历==
2019.10 - 至今       北京工商大学    教授      博士生导师

2012.10 - 2019.09     北京工商大学    副教授    硕士生导师

2011.07 - 2012.09     北京工商大学    讲师

2009.04 - 2011.06     清华大学        博士后

2005.09 - 2009.04     北京科技大学    工学博士

2016.02 - 2017.02     美国宾夕法尼亚大学医学院放射系 访问学者

==主讲课程==
信号分析与处理，图像工程，模式识别技术与应用等。

==研究领域==
模式识别，图像处理，计算机视觉

==学术成果==

近年来已在科学出版社出版学术专著3部，在Optics Letters、Optics Communications、Optical Engineering、Journal of Visual Communication and Image Representation、电子学报、ICPR等国际国内期刊与会议发表论文60余篇，其中SCI收录14篇。申请国家发明专利23项，其中已授权17项，获批软件著作权9项。主持国家自然科学基金面上项目2项，北京市“高创计划”青年拔尖人才资助项目1项，北京市自然基金-北京市教委重点联合基金项目1项，北京市自然科学基金面上项目1项，北京市属高等学校高层次人才引进与培养计划项目1项，北京市组织部优秀人才培养资助项目1项，中国博士后科学基金面上项目1项，国家留学基金委资助项目1项，北京工商大学青年教师科研启动基金项目1项。目前为中国教育发展战略学会人工智能与机器人教育专业委员会常务理事，中国人工智能学会生物信息学与人工生命专委会委员，中国自动化学会、中国电子学会和中国人工智能学会高级会员，CCF YOCSEF委员，Optics Letters、Optics Communications、IEEE Transactions on Instrumentation & Measurement等国际期刊审稿人，国家自然科学基金函评专家。
==学术成果==
=== 专著 ===

王瑜，[[《局部边缘模式及应用》]]，科学出版社，2020；

王瑜，[[《荧光显微图像3D重建技术与应用》]]，科学出版社，2015；

王瑜，《多模态生物特征识别——基于人脸与人耳信息》，科学出版社，2013。

=== 文章 ===

[1] Yu Wang*, Xi Liu, Chongchong Yu. Assisted Diagnosis of Alzheimer’s Disease Based on Deep Learning and Multimodal Feature Fusion [J]. Complexity, 2021. 

[2] Changchun Zhang, Qingjie Zhao, Yu Wang. Hybrid adversarial network for unsupervised domain adaptation[J]. Information Sciences, 2020, 514: 44-55. (SCI, EI)

[3] Changchun Zhang, Qingjie Zhao, Yu Wang. Transferable attention networks for adversarial domain adaptation[J]. Information Sciences, 2020, 539: 422-433. (SCI, EI) 

[4] Yu Wang*, Changsheng Li, Ting Zhu, Jingyang Zhang. Multimodal brain tumor image segmentation using WRN-PPNet [J]. Computerized Medical Imaging and Graphics. 2019, 75: 56-65.(SCI, EI)

[5] Wang Yu*, Zhang Na, et al. Magnetic Resonance Imaging Study of Gray Matter Based on XGBoost in Schizophrenia [J]. Journal of Integrative Neuroscience, 2018, 17(4): 331-336. (SCI, EI)

[6] Yu Wang*, Na Zhang, Huaixin Yan. Using Local Edge Pattern Descriptors for Edge Detection [J]. International Journal of Pattern Recognition and Artificial Intelligence, 2018, 32(3): 1-16. (SCI, EI)

[7] Yu Wang*, Xiaomeng Chen, Qiang Cai, Haisheng Li. Common Green Plants Recognition Based on Wavelet Transformation and Varied Local Edge Patterns [J]. International Journal of Pattern Recognition and Artificial Intelligence, 2018, 32(12): 1850045-1-14. (SCI, EI))

[8] Yu Wang*, Yongsheng Zhao, et al. A varied local edge pattern descriptor and its application to texture classification. Journal of Visual Communication and Image Representation, 2016, 34(1): 108-117. (SCI, EI)

[9] Yu Wang*, Huan Jiang. Three-dimensional reconstruction of microscopic images using different order intensity derivatives. Optical Engineering, 2015, 54(2): 023103-023103. (SCI, EI)

[10] Yu Wang*, Yongsheng Zhao, et al. Texture Classification Using Rotation Invariant Models on Integrated Local Binary Pattern and Zernike Moments. EURASIP Journal on Advances in Signal Processing, 2014, 182(1): 1-12. (SCI, EI)

[11] Yu Wang*, Qionghai Dai, et al. Blind deconvolution subject to sparse representation for fluorescence microscopy. Optics Communications, 2013, 286(1): 60-68. (SCI, EI)

[12] Yu Wang*, Dejian He, et al. Multimodal biometrics approach using face and ear recognition to overcome adverse effects of pose changes. Journal of Electronic Imaging, 2012, 21(4): 043026-043026. (SCI, EI)

[13] Wang Yu*, Ji Xiangyang, Dai Qionghai. Fourth-order Oriented Partial-differential Equations for Noise Removal of Two-photon Fluorescence Images. Optics Letters, 2010, 35(17): 2943-2945. (SCI, EI)

[14] Wang Yu*, JI XiangYang, Dai QiongHai. Key Technologies of Light Field Capture for 3D Reconstruction in Microscopic Scene. Science in China Series F: Information Sciences, 2010, 53(10): 1917-1930. (SCI, EI)

[15] Yu Wang*, Changsheng Li, Ting Zhu, Chongchong Yu. A Deep Learning Algorithm for Fully Automatic Brain Tumor Segmentation. In proceedings of International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 14th-19th, 2019. (EI)

[16] Yu Wang*, Huan Jiang. Light field creating and imaging with different order intensity derivatives. SPIE/COS Photonics Asia 2014: Optoelectronic Imaging and Multimedia Technology III, Beijing, China, October 9-11, 2014. (EI)

[17] Yu Wang*, Zhichun Mu, Hui Zeng. Block-based and Multi-resolution Methods for Ear Recognition Using Wavelet Transform and Uniform Local Binary Patterns. The 19th International Conference on Pattern Recognition (ICPR 08), Tampa, USA, 2008. (EI)

[18] 王瑜*, 穆志纯, 付冬梅. 基于小波变换和规范型纹理谱描述子的人耳识别研究. 电子学报, 2010, 38(1): 239-243. (EI)

=== 专利与软著 ===

[1] 戴琼海, 王瑜.一种微观光场采集与三维重建方法及装置. (授权)

[2] 戴琼海, 王瑜. 一种图像去噪方法(基于四阶偏微分方程与对比度增强).(授权)

[3] 王瑜等. 基于盲反卷积和稀疏表示的荧光显微图像复原方法和装置. (授权)

[4] 王瑜等. 一种人脸检测与跟踪方法及系统. (授权)

[5] 王瑜等. 相似图像分类方法及系统. (授权)

[6] 王瑜等. 基于局部二值模式和Zernike矩的纹理图像分类方法及系统. (授权)

[7] 王瑜等. 基于局部边缘模式的纹理图像分类方法及系统. (授权)

[8] 王瑜. 图像局部边缘模式与非边缘模式判别方法及其判别装置. (授权)

[9] 王瑜等. 基于图像强度各阶导数的荧光显微图像3D重建方法及装置. (授权)

[10] 王瑜等. 基于空间变化点扩散函数的荧光显微图像重建方法及系统. (授权)

[11] 王瑜等. 基于复合正则化技术的荧光显微图像3D重建方法及装置. (授权).

[12] 王瑜等. 一种基于多尺度多分辨率的方形算子边缘提取方法及系统.(授权)

[13] 王瑜等. 基于改进的分裂Bregman算法的荧光显微图像复原方法和装置.

[14] 王瑜. 一种基于颜色-形状特征的自动目标跟踪方法及系统.

[15] 王瑜等. 一种基于圆形算子的图像边缘提取方法和装置. (授权)

[16] 王瑜等. 基于多通路卷积神经网络的图像分类方法及系统.

[17] 王瑜等. 一种基于宽残差金字塔池化网络的图像分类方法及系统. (授权)

[18] 王瑜等. 基于LP正则化的多任务学习分类方法与系统. (授权)

[19] 王瑜等. 基于视觉显著性检测的高纹理图像分类方法及系统.

[20] 王瑜等. 基于分线性整数规划的卷纸分切和排产优化方法及系统.

[21] 王瑜等. 全自动机械设备安装泄露检测方法及装置. (授权)

[22] 王瑜等. 基于频率调谐全局显著度和深度学习的图像分割方法及系统. (授权)

[23] 王瑜等. 绿色植物识别系统V1.0. 登记号: 2014SR177053.

[24] 王瑜等. 基于视频文件的车牌分析系统V1.0. 登记号: 2014SR161214.

[25] 王瑜等. 荧光显微图像显示与分析系统V1.0. 登记号: 2015SR150801.

[26] 王瑜等. 人脸识别门禁系统V1.0. 登记号: 2016SR235108.

[27] 王瑜等. 荧光显微图像显示与分析系统V2.0. 登记号: 2016SR226823.

[28] 王瑜等. 卷纸分切系统软件V1.0. 登记号: 2018SR150801.

[29] 王瑜等. 基于骨架与色调的铅笔画生成系统V1.0. 登记号: 2020SR1066143.

[30] 王瑜等. 阿尔茨海默病辅助诊断系统V1.0版. 登记号: 2020SR1066161.

==科研项目==

[1] 融合结构和功能磁共振成像的阿尔茨海默型痴呆辅助鉴别关键技术研究, 国家自然科学基金面上资助项目(No. 61671028) (已结题)；

[2] 荧光显微样本3D重建与分析关键技术研究, 国家自然科学基金面上资助项目(No. 61171068) (已结题) ；

[3] 基于多模态磁共振成像与深度学习的脑肿瘤辅助诊断关键技术研究，北京市自然科学基金-北京市教育委员会科技计划重点项目联合项目(No. KZ202110011015) (在研)；

[4] 免于释文解释的精细图像分类新方法研究, 北京市自然科学基金面上资助项目(No. 4162018) (已结题)；

[5] 绿色植物物种识别关键技术研究, 北京市“高创计划”青年拔尖人才支持计划项目(No. 2014000026833ZK14) (已结题)；

[6] 计算机视觉中从属层对象分类关键技术研究, 北京市属高等学校高层次人才引进与培养计划项目(No.CIT&TCD201504010) (已结题)；

[7] 3D光场显微镜基础理论研究, 北京市优秀人才培养资助项目(No. 2012D005003000010) (已结题)；

[8] 基于磁共振成像的脑部疾病的分析与诊断, 国家留学基金委公派高级研究学者及访问学者资助项目(No. 201508110012) (已结题)；

[9] 微观光场高质量获取与三维重建研究，中国博士后科学基金面上资助项目 (No. 20100480273) (已结题)；

[10] 薄样本显微图像3D重建与分析，北京工商大学青年教师科研启动基金项目(No. QNJJ2012-22) (已结题)。

==获奖情况==

[1] 2018年，荣获北京工商大学科学技术奖三等奖，排名第1；

[2] 2017年，荣获北京工商大学研究生教育教学成果奖二等奖，排名第1；

[3] 2010年，成果《光场处理理论与光场系统》通过教育部科技成果鉴定，排名第10；

[4] 2019年，荣获北京工商大学优秀研究生导师称号；

[5] 连续4年指导研究生荣获国家奖学金(2015 姜欢，2016 闫怀鑫，2017 张娜，2018 陈肖蒙)，1人次荣获北京工商大学和北京市普通高等学校优秀毕业生(2016 闫怀鑫)；

[6] 2015年，院级优秀班主任，所带班级荣获校级优良学风班，北京市优秀班集体；

[7] 2018年，作为指导教师带队参加国际虚拟现实技术及应用创新大赛(IVRTC2018)，荣获国际三等奖1组，潜质奖1组，优秀指导教师称号；

[8] 2014年，作为指导教师带队参加 “中国软件杯”大学生软件设计大赛，荣获北京市一等奖1组，二等奖1组，全国优秀奖1组，最佳学校组织奖，以及优秀指导教师称号；

[9] 2011年，作为指导教师参加全国大学生电子设计大赛，荣获北京市二等奖1组。
==社会任职==

[1] 2012-至今，IEEE (美国电气与电子工程师协会)，会员；

[2] 2013-至今，中国自动化学会，高级会员；

[3] 2015-至今，中国电子学会，高级会员；

[4] 2013-至今，中国人工智能学会，高级会员，生物信息学与人工生命专委会委员；

[5] 2019-至今，中国教育发展战略学会人工智能与机器人教育专业委员会常务理事；

[6] 2013-至今，中国计算机学会 YOCSEF，委员；

[7] 2012-至今，国家自然基金函评专家；

[8] 2010-至今，Optics Letters、Optics Communications、IEEE Transactions on Instrumentation & Measurement、Journal of Electronic Imaging等国际期刊审稿人；

[9] 2014.9-2016.2，国家自然科学基金委员会信息科学部兼聘。

Curriculum Vitae

Yu Wang

Email: wangyu@btbu.edu.cn

Tel.: +86-010- 68985506

Education and Employment

l Oct. 2019 ~ Present    Professor, Beijing Technology and Business University, China

l Oct. 2012 ~ Sep. 2019 Associate Professor, Beijing Technology and Business University, China

l Jul. 2011 ~ Sep. 2012 Lecturer, Beijing Technology and Business University, China

l Apr. 2009 ~ Jun. 2011  Postdoctor, Tsinghua University, China

l Sep. 2005 ~ Jan. 2009  Ph. D., University of Science and Technology Beijing, China

l Feb. 2016 ~ Feb. 2017  Visiting Scholar, University of Pennsylvania, USA

Research Interests

l Image processing

l Pattern recognition

l Computer vision

Projects

Principal Investigator

l Key Technologies Research on 3D Reconstruction of Fluorescence Microscopic Specimen. National Natural Science Foundation of China (No. 61171068)

l Key Technologies Research on aided discrimination of Alzheimer's disease fusing structural and functional magnetic resonance imaging. National Natural Science Foundation of China (No. 61671028)

l Key Technologies Research on Aided Diagnosis of Brain Glioma Based on Multi-model Magnetic Resonance and Deep Learning. Joint Project of Beijing Natural Science Foundation and Beijing Municipal Education Commission (No. KZ202110011015)

l New annotation-free methods research on fine-grained image categorization. Beijing Natural Science Foundation(No. 4162018)

l Analysis and Diagnosis for Human Brain Diseases based on Magnetic Resonance Imaging. Foundation of China Scholarship Council (No. 201508110012)

l Key Technologies Research on Object Categorization Belonging to Subordinate Level. The Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions (No. CIT&TCD201504010)

l Key Technologies Research on green plant recognition. Beijing Talents Fund (No. 2014000026833ZK14)

l Research on High-quality Acquisition and 3D Reconstruction for Microscopic Light Field. China Postdoctoral Science Foundation (No. 20100480273)                                                                                              

l Research on Basic Theories of 3D Light Field Microscope. Excellent Talents Training Foundation of Beijing (No. 2012D005003000010)

l 3D Reconstruction and Analysis on Microscopic Images of Thin Specimen. Research Foundation for Youth Scholars of Beijing Technology and Business University (No. QNJJ2012-22).

Participator

l Multi-dimension Media Perception and Understanding of Data Driven. National Natural Science Foundation of China (No. 61035002)  

l Research on Multimodal Biometrics Recognition Based on the Information Fusion of Face and Ear. National Natural Science Foundation of China (No. 60573058)  

l Research on Ear Recognition Technologies. National Natural Science Foundation of China (No. 60375002)  

Publications

Books

[1] Yu Wang. Local edge pattern and its application. China, Beijing: Science Press, 2020.10.

[2] Yu Wang. 3D reconstruction technologies and applications of fluorescence microscopic images. China, Beijing: Science Press, 2015.10.

[3] Yu Wang. Multi-modal biometrics recognition based on face and ear. China, Beijing: Science Press, 2013.12.

Papers

[1] Yu Wang*, Xi Liu, Chongchong Yu. Assisted Diagnosis of Alzheimer’s Disease Based on Deep Learning and Multimodal Feature Fusion [J]. Complexity, 2021. 

[2] Zhang Changchun, Zhao Qingjie, Wang Yu. Hybrid adversarial network for unsupervised domain adaptation[J]. Information Sciences, 2020, 514: 44-55.

[3] Zhang Changchun, Zhao Qingjie, Wang Yu. Transferable Attention Networks for Adversarial Domain Adaptation. Information Sciences, 2020, 539: 422-433.

[4] Yu Wang*, Changsheng Li, Ting Zhu, Jingyang Zhang. Multimodal brain tumor image segmentation using WRN-PPNet. Computerized Medical Imaging and Graphics. 2019, 75: 56-65.

[5] Wang Yu*, Zhang Na, et al. Magnetic Resonance Imaging Study of Gray Matter Based on XGBoost in Schizophrenia. Journal of Integrative Neuroscience, 2018, 17(4): 331-336.

[6] Yu Wang*, Na Zhang, Huaixin Yan. Using Local Edge Pattern Descriptors for Edge Detection. International Journal of Pattern Recognition and Artificial Intelligence, 2018, 32(3): 1-16.

[7] Yu Wang*, Xiaomeng Chen, Qiang Cai, Haisheng Li. Common Green Plants Recognition Based on Wavelet Transformation and Varied Local Edge Patterns. International Journal of Pattern Recognition and Artificial Intelligence, 2018, 32(12): 1850045-1-14.

[8] Yu Wang*, Yongsheng Zhao, et al. A varied local edge pattern descriptor and its application to texture classification. Journal of Visual Communication and Image Representation, 2016, 34(1): 108-117.

[9] Yu Wang*, Huan Jiang. Three-dimensional reconstruction of microscopic images using different order intensity derivatives. Optical Engineering, 2015, 54(2): 023103-023103.

[10] Yu Wang*, Yongsheng Zhao, et al. Texture Classification Using Rotation Invariant Models on Integrated Local Binary Pattern and Zernike Moments. EURASIP Journal on Advances in Signal Processing, 2014, 182(1): 1-12.

[11] Yu Wang*, Qionghai Dai, et al. Blind deconvolution subject to sparse representation for fluorescence microscopy. Optics Communications, 2013, 286(1): 60-68.

[12] Yu Wang*, Dejian He, et al. Multimodal biometrics approach using face and ear recognition to overcome adverse effects of pose changes. Journal of Electronic Imaging, 2012, 21(4): 043026-043026.

[13] Wang Yu*, Ji Xiangyang, Dai Qionghai. Fourth-order Oriented Partial-differential Equations for Noise Removal of Two-photon Fluorescence Images. Optics Letters, 2010, 35(17): 2943-2945.

[14] Wang Yu*, JI XiangYang, Dai QiongHai. Key Technologies of Light Field Capture for 3D Reconstruction in Microscopic Scene. Science in China Series F: Information Sciences, 2010, 53(10): 1917-1930.

[15] Yu Wang*, Changsheng Li, Ting Zhu, Chongchong Yu. A Deep Learning Algorithm for Fully Automatic Brain Tumor Segmentation. In proceedings of International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 14th-19th, 2019.

[16] Yu Wang*, Huan Jiang. Light field creating and imaging with different order intensity derivatives. SPIE/COS Photonics Asia 2014: Optoelectronic Imaging and Multimedia Technology III, Beijing, China, October 9-11, 2014.

[17] Yu Wang*, Zhichun Mu, Hui Zeng. Block-based and Multi-resolution Methods for Ear Recognition Using Wavelet Transform and Uniform Local Binary Patterns. The 19th International Conference on Pattern Recognition (ICPR), Tampa, USA, 2008.<ref>[https://www.btbu.edu.cn 北京工商大学]</ref>
==参考资料== 
{{reflist}}

[[Category:教授]]