赵建伟
sex
2
title
教授
department
理学院
college
college2
degree
博士
recruit":0,"firstDiscipline1
数学
secondaryDiscipline1
firstDiscipline2
secondaryDiscipline2
executive
理学院应数系主任
officePhone
mobilePhone
**
emailAddress
zhaojw@cjlu.edu.cn
businessAddress
格致中楼506室
individualResume
赵建伟,女,汉族,1977年11月出生,博士(后),教授, 数学硕士生导师。浙江省高校中青年学科带头人、浙江省151人才第三层次、理学院应用数学系主任、理学院智能计算与数据分析科研团队负责人。2006年6月获得中国科学院数学与系统科学研究院博士学位、韩国全北大学电子工程研究院博士后。担任中国人工智能学会知识工程与分布智能专业专业委员会委员、机器学习专业委员会通讯委员,浙江省数理医学学会生物医学数学专业委员会副主任。主要从事深度学习、模式识别与图像处理、视频追踪等方向,主持完成3项国家自然科学基金、3项浙江省自然科学基金项目、校企合作项目2项,并参与国家自然科学基金项目多项。在IEEE Transactions on Neural Networks and Learning Systems, Neural Networks, Information Sciences, Knowledge-Based Systems, Neurocomputing、Neural Computing and Applications等国内外期刊上发表学术论文60多篇,其中SCI检索论文30篇,授权发明专利9项。访问过韩国全北大学、澳大利亚斯文本科技大学、香港中文大学等高校。2009年开始招硕士研究生,2012年、2015年获得校优秀硕士生导师称号。目前指导硕士生毕业14名、7名在读,其中4人获得校优秀硕士学位论文。毕业硕士生主要去国内外高校攻读博士学位、或到上海、深圳、杭州等地的高科技公司从事算法工程师、数据分析师、图像分析师等科研管理工作,就业率100%。\r教育经历: \r2003/09-2006/06,中国科学院数学与系统科学研究院数学所,基础数学,博士 \r2000/09-2003/06,陕西师范大学,数学系,基础数学,硕士\r1996/09-2000/07,陕西师范大学,数学系,基础数学,学士\r研究工作经历: \r2017/12/16-2017/12/23 香港中文大学未来城市研究院\r2013/07-2013/08 澳大利亚斯文本科技大学 电子工程学院 访问 \r2011/03-2012/03 韩国全北大学 信息与通信工程学院 博士后\r2013/11-至今 中国计量大学,理学院应数系,教授 \r2008/11-2013.10 中国计量大学,理学院数学系,副教授 \r2006/07-2008/10, 中国计量学院,理学院数学系,讲师 \r
researchTopic
\r1. 主持浙江省自然科学基金项目一般项目:图像重建新方法:深度卷积神经网络逼近(NO. LY18F020018), 经费:10万元,2018.1.1-2020.12.31。\r2. 主持南京大学计算机软件新技术国家重点实验室开放课题:面向超分辨率图像重建的递归多关注深度网络研究,KFKT2019B07,赵建伟,经费:2万,2019.6.1-2021.5.31。
awards
1.“人工神经网络逼近复杂性问题研究”获浙江省高等学校科研成果奖二等奖,排名第2,2012年12月10日.\r2.2013年被评为浙江省中青年学科带头人。\r3.2015年被评为浙江省151人才工程第三层次。\r4.获2012年、2015年“优秀研究生导师” 荣誉称号。\r5.指导的硕士研究生王智慧获2012年校优秀硕士学位论文。\r6.2011年度校优秀科研工作者。
researchProject
1.国家自然科学基金面上项目:超分辨率图像重建:低秩稀疏表示与矩阵恢复非凸正则化方法(**),2016.1.1-2019.12.31,60万元。 \r2.国家自然科学基金青年项目:基于线性逆问题理论的正则化学习算法及其应用研究(**),2012.1.1-2014.12.31,28万元。\r3.国家自然科学基金专项项目-数学天元基金:关于von Neumann代数交叉积的研究(**),时间: 2010.1- 2010.12,3万。\r4.浙江省自然科学基金面上项目:面向高维数据的稀疏矩阵恢复算法与误差分析(LY14A010027),2014.1.1-2016.12.31,6万元。\r5.浙江省自然科学基金项目:距离空间上的神经网络插值与逼近的研究(批准号:Y**), 2011.1.1-2012.12.31,8万。\r6.校企项目:电路板元器件的检测与识别(H161259),技术开发,浙江涵普电力科技有限公司,2016.11.4-2017.3.31,20万元。\r
publications
学术论文:\r1.Jianwei Zhao, Taoye Huang, Zhenghua Zhou, Feilong Cao. A compact recursive dense convolutional network for image classification, Neurocomputing, 2020, 372: 8-16. (SCI, IF: 4.072)\r2.Jianwei Zhao, Taoye Huang, Zhenghua Zhou. Hyperspectral image super-resolution using recursive densely convolutional neural network with spatial constraint strategy. Neural Computing and Applications. DOI: 10.1007/s00521-019-04484-3\r3.Jianwei Zhao, Ningning Chen, Zhenghua Zhou. A Temporal Sparse Collaborative Appearance Model for Visual Tracking. Multimedia Tools and Applications, DOI: 10.1007/s11042-020-08630-1\r4.Jianwei Zhao, Yongbiao Lv, Zhenghua Zhou, Feilong Cao. A Novel Deep Learning Algorithm for Incomplete Face Recognition: Low-rank-recovery Network. Neural Networks, 2017, 94: 115–124. (SCI, IF: 5.225)\r5.Jianwei Zhao,Heping Hu,Feilong Cao. Image Super-Resolution via Adaptive Sparse Representation. Knowledge-Based Systems, 2017, 124:23-33. (SCI, IF:3.058)\r6.Jianwei Zhao, Chen Chen, Zhenghua Zhou, Feilong Cao. Single image super-resolution based on adaptive convolutional sparse coding and convolutional neural networks. Journal of Visual Communication and Image Representation, 2019, 58: 651-661.(SCI, IF: 2.259)\r7.Jianwei Zhao, Minshu Zhang, Zhenghua Zhou, Jianjun Chu, Feilong Cao. Automatic detection and classification of leukocytes using convolutional neural networks. Medical & Biological Engineering & Computing, 2017, 55(8): 1287-1301. (SCI, IF:2.224) \r8.Jianwei Zhao, Tiantian Sun, Feilong Cao. Image super-resolution via adaptive sparse representation and self-learning. IET Computer Vision, 2018, 12(5):753-761. (SCI, IF:1.132)\r9.Jianwei Zhao, Heping Hu, Zhenghua Zhou, Feilong Cao. Super-resolution reconstruction: using non-local structure similarity and edge sharpness dictionary.IET Image Processing,2017, 11(12): 1254 – 1264. (SCI, IF:1.472)\r10.Jianwei Zhao, Weidong Zhang, Feilong Cao. Robust object tracking using a sparse coadjutant observation model. Multimedia Tools and Applications, 2018, 77, 23: 30969-30991. \r11.Jianwei Zhao, Zhihui Wang, Feilong Cao, Dianhui Wang. A local learning algorithm for random weights networks. Knowledge-Based Systems, 74(1): 159-166. Jan. 2015 (SCI, IF: 4.514) \r12.Jianwei Zhao, Zhihui Wang, Dongsun Park. Online sequential extreme learning machine with forgetting mechanism. Neurocomputing, 87(15): 79-89. Jun. 2012, (SCI, IF:2.005)\r13.Jianwei Zhao, Zhihui Wang, Feilong Cao. Extreme learning machine with errors in variables. World Wide Web, 17(5): 1205-1216. Sep. 2014 (SCI, IF: 1.623)\r14.Jianwei Zhao, Dong Sun Park, Joonwhoan Lee, Feilong Cao. Generalized extreme earning machine on a metric space. Soft Computing, 16(9): 1503-1514. Sep. 2012, (SCI, IF:1.124)\r15.Jianwei Zhao, Zhenghua Zhou, Feilong Cao. Human face recognition based on ensemble of polyharmonic extreme learning machine. Neural Computing and Applications, 24: 1317-1326. May 2014. (SCI, IF: 1.763)\r16.Jianwei Zhao. Functional data learning by Hilbert feedforward neural networks. Mathematical Methods in the Applied Sciences, 35(17): 2111-2121. Nov. 2012. (SCI, IF:0.877)\r17.Jing Lu, Jianwei Zhao, Feilong Cao. Extended feed forward neural networks with random weights for face recognition. Neurocomputing, 136: 96-102. Jul. 2014. (SCI, IF: 2.005)\r18.Kankan Dai, Jianwei Zhao, Feilong Cao. A novel decorrelated neural network ensemble algorithm for face recognition. Knowledge-Based Systems, 89:541-552. Nov. 2015. (SCI, IF: 4.514) \r19.Kankan Dai, Jianwei Zhao, Feilong Cao, A novel algorithm of extended neural networks for image recognition, Engineering Applications of Artificial Intelligence, 2015, 42:57-66. (SCI, IF:3.13) \r20.Zhenghua Zhou, Weidong Zhang, Jianwei Zhao. Robust visual tracking using discriminative sparse collaborative map. International Journal of Machine Learning and Cybernetics, 2019, 10(11): 3201-3212 (SCI, IF:3.274)\r21.Zhenghua Zhou, Jianwei Zhao, Feilong Cao. A novel approach for fault diagnosis of induction motor with invariant character vectors. Information Sciences,2014, 281(1): 496-506. (SCI, IF:3.893)\r22.Zhenghua Zhou, Jianwei Zhao, Feilong Cao. Diagnosis of fatigue crack growth with recursive random weight networks. Computers and Electrical Engineering, 2014, 40: 2227-2235. (SCI, IF: 0.992)\r23.Zhenghua Zhou, Jianwei Zhao, Feilong Cao,Face recognition based on random weights network and quasi singular value decomposition, Emerging Intelligent Computing Technology and Applications, Communications in Computer and Information Science, 2013(375): 136-141.\r24.Zhenghua Zhou, Jianwei Zhao, Feilong Cao. Surface reconstruction based on extreme learning machine. Neural Computing and Applications, 2013,23(2): 283-292. (SCI, IF: 1.763)\r25.Yuehua Liu, Feilong Cao, Jianwei Zhao, Jianjun Chu. Segmentation of white blood cells image using adaptive location and iteration. IEEE Journal of Biomedical and Health Informatics, 2017, 21(6): 1644-1655. (SCI, IF: 3.936)\r26.Feilong Cao, Yuehua Liu, Zhen Huang, Jianjun Chu, Jianwei Zhao. Effective segmentations in white blood cell images using epsilon-SVR-based detection method,Neural Computing & Applications, 2019, 31(10): 6767-6780.\r27.Feilong Cao,Miaomiao Cai,Yuanpeng Tan, Jianwei Zhao. Image super- resolution via adaptive regularization and sparse representation. IEEE Transactions on Neural Networks and Learning Systems, 27(7): 1550-1561. Jul. 2016. (SCI, IF: 7.658)\r28.Feilong Cao, Jiaying Chen, Jianwei Zhao, Zhenghua Zhou. Recovering low-rank and sparse matrix based on the truncated nuclear norm. Neural Networks, 2017, 85: 10-20. (SCI, IF: 5.225) \r29.Feilong Cao, Xinshan Feng, Jianwei Zhao. Sparse representation for robust face recognition by dictionary decomposition. Journal of Visual Communication and Image Representation, 2017, 46: 260–268.\r30.Feilong Cao, Miaomiao Cai, Jianjun Chu, Jianwei Zhao, Zhenghua Zhou. A novel segmentation algorithm for nucleus in white blood cells based on low-rank representation. Neural Computing & Applications, 2017, 28: S503-S511.\r31.Feilong Cao, Heping Hu, Jing Lu, Jianwei Zhao, Zhenghua Zhou, Jiao Wu. Pose and illumination variable face recognition via sparse representation and illumination dictionary. Knowledge-Based Systems, 2016, 107: 117-128. (SCI二区) \r32.Feilong Cao, Xing Xing, Jianwei Zhao. Learning rates of support vector machine classifier for density level detection. Neurocomputing, 82: 84-90, Apr. 2012. (SCI, IF: 2.005)\r33.张伟东,赵建伟,周正华,曹飞龙. 基于特征选择与时间一致性稀疏外观模型的目标追踪算法. 模式识别与人工智能,2018, 31(3): 245-255.\r34.吕永标,赵建伟,曹飞龙. 基于复合卷积神经网络的图像去噪算法,模式识别与人工智能,2017, 30(2): 97-105.\r35.赵建伟,周正华,曹飞龙. 一种基于调和随机权网络与曲波变换的图像分类方法,模式识别与人工智能,2014, 27(6): 2014,:509-516.\r\r发明专利:\r1.赵建伟,张敏淑,曹飞龙,周正华,冯爱明,楚建军.一种基于深度学习的白细胞五分类方法,发明专利,专利号:ZL5.2, 2018.\r2.赵建伟,吕永标,曹飞龙,周正华. 一种基于卷积网络特征提取的人脸识别方法,发明专利,专利号:ZL6.8,2019.\r3.曹飞龙,刘月华,黄震,楚建军,赵建伟,周正华. 一种白细胞定位和迭代分割方法,发明专利,专利号:ZL7.X, 2018.\r4.曹飞龙,怀听听,赵建伟,周正华,冯爱明,楚建军. 一种基于随机森林的白细胞五分类方法,发明专利,专利号:ZL 4.1, 2018.\r5.曹飞龙,冯鑫山,赵建伟,周正华. 一种基于字典分解和稀疏表示的鲁棒人脸识别方法,发明专利,专利号:ZL 9.5, 2019.\r6.蔡苗苗,楚建军,曹飞龙,赵建伟,周正华.一种基于直方图阈值及低秩表示的白细胞细胞核分割方法,2018.12.14,专利号:9.1, 2019\r7.黄震,孔巢城,曹飞龙,赵建伟,周正华.一种基于边界的白细胞分割评价标准,专利号: 2018.09.07,3.5, 2019.\r8.陆晶,楚建军,曹飞龙,赵建伟,周正华. 血液白细胞显微图像的随机权网络分割方法,2018.12.1,专利号:5.9, 2019.\r9.黄震,楚建军,曹飞龙,赵建伟,周正华.一种基于多特征非 线性组合的白细胞分割方法,2018.12.14,专利号:9.4, 2019.
others
毕业硕士生在国内外高校攻读博士、或到高科技公司从事算法工程师、数据分析师、图像分析师等科研管理工作
correlation
researchDirection1
深度学习
researchDirection2
模式识别与图像处理
researchDirection3
视频追踪
researchDirection4
大数据处理
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中国计量大学理学院导师教师师资介绍简介-赵建伟
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