刘伟锋


系        属：自动化系
学        位：博士
职        称：教授
导师类别：博士生导师
专        业：模式识别与智能系统
电子邮箱：liuwf@upc.edu.cn
通讯地址：山东省青岛市黄岛区长江西路66号
[个人主页]

  

研究方向

  • 机器学习算法研究
    • 机器学习中的流形结构分析：利用样本数据分布的局部结构，促进模式识别中特征提取、分类器设计等的性能
    • 多视角学习算法研究：探索多源数据、多视角特征的协同学习，提高机器学习算法及系统性能
    • 稀疏表达及其应用研究：探索不同应用场景的稀疏特征表示方法，研究高效的稀疏编码算法
    • 深度学习算法研究：图卷积神经网络算法，对抗生成网络算法
    • 跨域机器学习算法研究：迁移学习算法、元学习算法
  • 智能信息处理系统设计
    • 多媒体信息处理系统设计
    • 智能便携式应用系统设计
    • 工业互联网信息再感知系统设计
    • 图像分类及标注系统设计
    • 动作识别及行为分析系统设计
  • 人工智能算法在工业互联网、地球物理勘探、智慧油气田开发中的应用研究
    • 工业互联网中的信息理解与应用
    • 油藏数值模拟与优化
    • 地震资料分析与处理

      

    教育经历

  • 1998.09-2002.07，中国科学技术大学，自动化系，自动控制、工商管理双学士学位
  • 2002.09-2007.06，中国科学技术大学，自动化系，模式识别与智能系统，博士学位

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    工作经历

  • 2007.07-至今，历任中国石油大学（华东），讲师、副教授、教授

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    学术兼职

  • IEEE高级会员
  • IEEE SMC协会感知计算技术委员会主席
  • ACM会员
  • ACM SIGMM中国分会会员
  • CCF高级会员
  • CCF计算机视觉专委会委员
  • 《Neural Processing Letters》编委(Associate editor)
  • 《Signal Processing》、《IET Computer Vision》、《Neurocomputing》、《Remote Sensing》 客座编辑（Guest editor）

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    主讲课程

  • 模式识别、数字图像处理等研究生、本科生课程

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    指导研究生及博士后

  • 毕业研究生
    • 李乔楠(硕士2020届)，碳纤维抽油杆显微图像检测分析系统的研究与开发， 光大银行青岛分行
    • 傅司超(硕士2020届) ，基于图卷积神经网络的半监督分类算法研究， 澳门大学攻读博士
    • 冯冠华(硕士2020届) ，基于 Hessian 正则化的行人再识别算法研究， 云从科技
    • 伊丽莎(硕士2019届) ，基于矩阵回归的图像分类算法研究 ，北京某厂
    • 马学琦(硕士2019届) ，基于p-Laplacian的图像分类算法研究， 墨尔本大学攻读博士
    • 张振清(硕士2018届) ，基于广义Hough变换的直线道路检测算法研究 ，歌尔声学股份有限公司
    • 杨兴浩(硕士2018届) ，基于典型相关分析的多视角图像识别算法研究， 悉尼科技大学攻读博士
    • 马腾洲(硕士2017届) ，基于Auto-Encoder的图像识别算法研究 ，青岛通产智能科技股份有限公司
    • 张连波(硕士2017届) ，基于交互学习的生理情感信号分析， 悉尼科技大学攻读博士
    • 李阳*(硕士2016届) ，协同训练中的流形正则化及其在分类中的应用研究 ，山东省公共安全技术防范监理中心
    • 张会敏(硕士2015届)，特征向量的稀疏性分析及其应用研究 ，北纬通信科技南京有限责任公司
    • 刘红丽(硕士2015届) ，多视角学习在智能信息处理中的若干应用研究， 歌尔声学股份有限公司
    • 宋彩风*(硕士2013届)，基于视觉感知机制的人脸表情分析， 广饶县民生热线综合服务中心
  • 在读
    • 博士2020级 昝畅通
    • 博士2019级 许睿
    • 硕士2020级 潘婷、刘东凯、许仁杰、蔡玉颖、潘丽丽、李家兴
    • 硕士2019级 彭旭阳、王飞、吕云雪、刘瑶
    • 硕士2018级 潘宜辰、李金凤、卜祥蕊#、赵贵啸#

      

    承担项目


    承担国家自然科学基金面上项目、青年基金等多项科研项目。

      

    论文


    近年发表学术论文近百篇，其中10篇论文入选ESI高被引论文，3篇入选ESI热点论文。

  • S. Fu, W. Liu, Y. Zhou, D. Tao, and C. Xu, “Dynamic Graph Learning Convolutional Networks for Semi-supervised Classification”, ACM Transactions on Multimedia Computing Communications and Applications, in press
  • W. Liu, S. Fu, Y. Zhou, Zh.-J. Zha, and L. Nie, “Human Activity Recognition by Manifold Regularization Based Dynamic Graph Convolutional Networks”, Neurocomputing, in press.
  • X. Yang, W. Liu, W. Liu, and D. Tao, “A Survey on Canonical Correlation Analysis”, IEEE Transactions on Knowledge and Data Engineering, 10.1109/TKDE.2019.2958342.
  • J. Li, W. Liu, Y. Zhou, D. Tao, and L. Nie, “Domain Adaptation with Few Labeled Source Samples by Graph Regularization,” Neural Processing Letters, 51(1): 23-39, 2020. 10.1007/s11063-019-10075-z.
  • S. Fu, W. Liu, D. Tao, Y. Zhou, and L. Nie, “HesGCN: Hessian Graph Convolutional Networks for Semi-Supervised Classification”, Information Sciences, 514: 484-498,2020. 10.1016/j.ins.2019.11.019.
  • W. Liu, X. Ma, Y. Zhou, D. Tao, and J. Cheng, “p-Laplacian Regularization for Scene Recognition,” IEEE Trans. on Cybernetics, 49(8):2927-2940, 2019. 10.1109/TCYB.2018.2833843.(ESI Highly Cited Papers)
  • Q. Wang, J. Yu, T. Liu, and W. Liu, “ Visual Domain Adaptation and Generalisation,” IET Computer Vision, 13(2): 87-89, 2019.(Editorial)
  • X. Ma, W. Liu, S. Li, D. Tao, and Y. Zhou, “Hypergraph -Laplacian Regularization for Remotely Sensed Image Recognition”, IEEE Trans. on Geoscience and Remote Sensing, 57(3): 1585-1595, 2019.(ESI Highly Cited Papers)
  • C. L. P. Chen, X. You, X. Gao, T. Liu, F. Murtagh, and W. Liu, “Advances in Data Representation and Learning for Pattern Analysis,” Neurocomputing, 348: 1-2, 2019, 10.1016/j.neucom.2018.08.084.(Editorial)
  • X. Tian, W. Liu, and F. Murtagh, “Data Mining in Human Activity Analysis,” Signal Processing, 147: 247-248, 2018. (Editorial)
  • W. Liu, X. Yang, D. Tao, J. Cheng, and Y. Tang, “Multiview dimension reduction via Hessian multiset canonical correlations,” Information Fusion, 41: 119-128, 2018.(ESI Highly Cited Papers)
  • X. Yang, W. Liu, D. Tao, J. Cheng, “Canonical Correlation Analysis Networks for Two-view Image Recognition”, Information Sciences, 385-386: 338-352, 2017.(ESI Highly Cited Papers)
  • Y. Guo, L. Li, W. Liu, J. Cheng, D. Tao, “Multiview Cauchy Estimator Feature Embedding for Depth and Inertial Sensor-Based Human Action Recognition”, IEEE Trans. on Systems, Man, and Cybernetics: Systems, 47(4): 617-627, 2017.
  • W. Liu, Z. Zha, Y. Wang, K. Lu, and D. Tao, “p-Laplacian Regularized Sparse Coding for Human Activity Recognition,” IEEE Trans. on Industrial Electronics, 63(8): 5120-5129, 2016.(ESI Hot Papers,ESI Highly Cited Papers)
  • W.Liu, H.Zhang, D.Tao, Y.Wang, K.Lu, “Large-Scale Paralleled Sparse Principal Component Analysis”, Multimedia Tools and Applications, 75(3): 1481-1493, 2016. (ESI Highly Cited Papers)
  • W.Liu, H.Liu, D.Tao, Y.Wang, K.Lu, “Multiview Hessian regularized logistic regression for action recognition”,Signal Processing, 110: 101-107, 2015. (ESI Hot Papers)
  • W. Liu, Y. Li, X. Lin, D. Tao, and Y. Wang, “Hessian regularized co-training for social activity recognition,” PLOS One, 9(9): e108474, 2014. (ESI Highly Cited Papers)
  • W. Liu, D. Tao, J. Cheng, and Y. Tang, “Multiview Hessian Discriminative Sparse Coding for Image Annotation,” Computer Vision and Image Understanding, 118: 50-60, 2014. (ESI Highly Cited Papers)
  • W. Liu and D. Tao, “Multiview Hessian Regularization for Image Annotation,” IEEE Trans. on Image Processing, 22: 2676-2687, 2013. (ESI Hot Papers,ESI Highly Cited Papers)
  • D. Tao, L. Jin, W. Liu, and X. Li, “Hessian Regularized Support Vector Machines for Mobile Image Annotation on the Cloud”. IEEE Trans. on Multimedia, 15(4): 833-844, 2013. (ESI Highly Cited Papers)
  • G. Feng, W. Liu, S. Li, D. Tao, and Y. Zhou, “Hessian regularized multi-task dictionary learning for Remote Sensing Image Recognition,” IEEE Geoscience and Remote Sensing Letters, 16(5): 821-825, 2019.
  • S. Fu, W. Liu, S. Li, and Y. Zhou, “A Two-Order Graph Convolutional Networks for Semi-Supervised Classification,” IET Image Processing, 13: 2763-2771,2019, 10.1049/iet-ipr.2018.6224.
  • X. Ma, W. Liu, D. Tao, and Y. Zhou, “Ensemble p-Laplacian Regularization for Remote Sensing Image Recognition,” Cognitive Computation, 11: 841-854,2019, 10.1007/s12559-019-09637-z.
  • G. Feng, W. Liu, D. Tao, and Y. Zhou, “Hessian regularized distance metric learning for people re-identification,” Neural Processing Letters, 50: 2087-2100,2019, 10.1007/s11063-019-10000-4.
  • X. Ma, D. Tao, and W. Liu, “Effective human action recognition by combining manifold regularization and pairwise constraints,” Multimedia Tools and Applications,78: 13313-13329, 2019. 10.1007/s11042-017-5172-1.
  • S. Fu, W. Liu, Y. Zhou, and L. Nie, “HpLapGCN: Hypergraph p-Laplacian Graph Convolutional Networks,” Neurocomputing, 362: 166-174, Oct. 2019.
  • W. Liu, L. Zhang, D. Tao, and J. Cheng, “Reinforcement Online Learning for Emotion Prediction by Using Physiological Signals”, Pattern Recognition Letters, 107: 123-130, 2018
  • W.Liu, T.Ma, Q.Xie, D.Tao, and J. Cheng, “LMAE: A Large Margin Auto-Encoders for Classification”, Signal Processing, 141: 137-143, 2017.
  • W.Liu, Z. Zhang, S. Li, and D. Tao, “Road Detection by Using a Generalized Hough Transform,” Remote Sensing, 9(6): 590, 2017.
  • W. Liu, L. Zhang, D. Tao, and J. Cheng, “ Support Vector Machine Active Learning by Hessian Regularization,” Journal of Visual Communication and Image Representation, 49: 47-56, 2017.
  • X. Yang, W. Liu, D. Tao, J. Cheng, and S. Li, “Multiview Canonical Correlation Analysis Networks for Remote Sensing Image Recognition,” IEEE Geoscience and Remote Sensing Letters, 14(10): 1855-1859, 2017.
  • W. Liu, Z. Zhang, X. Chen, S. Li, and Y. Zhou, “Dictionary Learning Based Hough Transform for Road Detection in Multispectral Image,” IEEE Geoscience and Remote Sensing Letters, 14(12): 2330-2334, 2017.
  • D. Tao, X. Yang, W. Liu, S. Sun, Y. Guo, Y. Yu, J. Pang, “Cauchy Estimator Discriminant Learning for RGB-D Sensor-based Scene Classification”, Multimedia Tools and Applications, 76(3): 4471-4489, 2017.
  • T.-S.Chua,X.He,W. Liu, M.Piccardi, Y.Wen,D. Tao,“Big Data Meets Multimedia Analytics”, Signal Processing, 124: 1-4, 2016. (Editorial)
  • W. Liu, H. Liu, and D. Tao, “Hessian regularization by patch alignment framework,” Neurocomputing, 204: 183-188, 2016.
  • W. Liu, T. Ma, D. Tao, J. You, “HSAE: A Hessian Regularized Sparse Auto-Encoders”, Neurocomputing, 187: 59-65, 2016.
  • W. Liu, H. Liu, D.T ao, Y. Wang, K.Lu, “Manifold regularized kernel logistic regression for web image annotation”,Neurocomputing, 172: 3-8, 2016.
  • W. Liu, Y. Li, D. Tao, and Y. Wang, “A general framework for co-training and its applications,” Neurocomputing, 167: 112-121, 2015.

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    专利


    申请国家发明专利10项（授权6项）

  • 一种基于典型相关分析网络的二视角图像识别方法，国家发明专利，ZL201610663936.1，2019.
  • 一种基于多视角典型相关分析的人脸识别方法及其系统, 国家发明专利，ZL201610055275.4，2019.
  • 一种智能导盲方法，国家发明专利，ZL201610012203.1, 2018.
  • 一种智能导盲装置及安装有该装置的导盲杖，国家发明专利，ZL201610010270.X, 2018.
  • 一种基于自编码的物体识别方法, 国家发明专利，ZL201610055128.7, 2018.
  • 一种基于高阶图结构p-Laplacian稀疏编码的数字图像标记方法，国家发明专利，ZL201510632014.X, 2017.