基本信息

吕娜 博士 教授 

博士生导师

硕士生导师

email:lvna2009@mail.xjtu.edu.cn

办公室:科学馆409

西安交通大学电信学院系统工程研究所

研究领域

统计图像分析、模式识别

机器学习、深度学习

脑机接口

大数据处理

智能机器人

主要任职

陕西省机器人先进控制工程实验室主任

担任国家自然科学基金通讯评议专家

担任国内外知名期刊IEEE Transactions on Neural Systems & Rehabilitation Engineering, Computer Methods and Programs in Biomedicine,IET System Biology, Pattern Recognition Letters, Biomedical Signal Processing and Control,Measurement,上海交通大学学报,西安交通大学学报等审稿人。

教育经历

1998年9月—2002年7月  西安交通大学机械学院机械工程及自动化系  本科、工学学士

2002年9月—2008年12月 西安交通大学电信学院系统工程研究所        工学博士

2011年4月—2013年4月    美国University of Rochester                         博士后

论文期刊

[1]     Lu Na*, Yin Tao, Jing Xue. Deep Learning Solutions for Motor Imagery Classification: A Comparison Study, IEEE International Winter Conference on Brain-Computer Interface, Korea, 2020.

[2]     Lu Na*, Yin Tao, Jing Xue. A Temporal Convolution Network Solution for EEG Motor Imagery Classification. 19th IEEE International Conference on BioInformatics and BioEngineering, 2019 (Acceptance rate: 33%).

[3]     Shi Xiahao, Lu Na*, Cui Zhiyan. Smoke detection based on dark channel and convolutional neural networks. IEEE Internatinal Conference on Big Data and Information Analytics, 2019. 

[4]     Sun Lei, Feng Zuren, Lu Na, Wang Baichen, Zhang Wenjun. An advanced bispectrum features for EEG-based motor imagery classification. Expert Systems with Applications, 131: 9-19, 2019. (SCI, IF: 4.292)

[5]     Luo Jing, Feng Zuren, Lu Na*. Spatio-temporal discrepancy feature for classification of motor imageries. Biomedical Signal Processing and Control,  2019, 47:137-144 (SCI  WOS:000449134500014, IF: 3.063)

[6]     Lu Na*, Wu Yidan, Feng Li, Song Jinbo. Deep Learning for Fall Detection: 3D-CNN Combined with LSTM on Video Kinematic Data. IEEE Journal of Biomedical and Health Informatics, 23(1): 314-323, 2019 (SCI, IF: 3.85)

[7]     Zhiyan Cui, Na Lu, Xue Jing, Xiahao Shi. Fast Dynamic Convolutional Neural Networks for Visual Tracking. Asian Conference on Machine Learning, PMLR 95:770-785, 2018 (Acceptance rate: 24.8%)

[8]     Wang Jie, Feng Zuren, Lu Na, Luo Jing. Toward optimal feature and time segment selection by divergence method for EEG signals classification. Computers in Biology and Medicine, 97: 161-170, 2018 (SCI WOS:000435623700016 , IF: 2.115)

[9]     Chen Badong, Li Yuanhao, Dong Jiyao, Lu Na, Qin Jing. Common spatial patterns based on the quantized minimum error entropy criterion. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2018In press (SCI, IF: 5.131)

[10]  Jia Feng, Lei Yaguo, Lu Na, Xing Saibo. Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization. Mechanical Systems and Signal Processing, 110: 349-367, 2018 (SCI, IF: 4.525)

[11] Wang Jie, Feng Zuren, Lu Na, Sun Lei, Luo Jing. An information fusion scheme based common spatial pattern method for classification of motor imagery tasks. Biomedical Signal Processing and Control, 4610-172018 (SCI  WOS:000447109800003, IF: 3.063)

[12] Chen Badong, Wang Xin, Lu Na, Wang Shiyuan, Cao Jiuwen, Qin Jing. Mixture correntropy for robust learning. Pattern Recognition, 79(7): 318-327,2018 (SCI, IF: 4.991)

[13] Sun Lei, Feng Zuren, Chen Badong, Lu Na*. A contralateral channel guided model for EEG based motor imagery classification. Biomedical Signal Processing and Control, 41: 1-9, 2018 (SCI WOS:000425572800001, IF: 3.063)

[14] Wang Jie, Feng Zuren, Lu Na. Feature extraction by common spatial pattern in frequency domain for motor imagery tasks classification. Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017, Chongqing, China, 5883-5888.

[15] Lu Na*, Ren Xiaodong, Song Jinbo, Wu Yidan. Visual guided deep learning scheme for fall detection. IEEE Conference on Automation Science and Engineering, 2017

[16] Lu Na*, Li Tengfei, Ren Xiaodong, Miao Hongyu. A Deep Learning Scheme for Motor Imagery Classification based on Restricted Boltzmann Machines. IEEE Transaction on Neural Systems & Rehabilitation Engineering, 25(6): 566-576, 2017 (SCI, IF: 3.478)

[17] Wang Yulin, Lu Na, Miao Hongyu. Structural identifiability of cyclic graphical models of biological networks with latent variables. BMC Systems Biology, 10(1), 2016 (SCI, IF: 2.213)

[18] Luo Jing, Feng Zuren, Zhang Jun, Lu Na*. Dynamic frequency feature selection based approach for classification of motor imageries. Computers in Biology and Medicine, 75: 45-53, 2016, (SCI WOS:000380623100006 , IF: 2.115)

[19] Lu Na, Miao Hongyu. Clustering tree-structured data on Manifold.IEEE Transaction on Pattern Analysis and Machine Intelligence, 38(10): 1956-1968, 2016 (SCI WOS:000384240600003, IF: 17.730)

[20] Lu Na, Silva Jharon N., Gu Yu, Wu Hulin, Gelbard Harris A., Dewhurst Stephen, Miao Hongyu. Capillary extraction by detecting polarity in circular profiles. IET Image Processing, 10(5): 339-348, 2016 (SCI WOS:00037395380000, IF: 1.044 )

[21] Jia Feng, Lei Yaguo, Lin Jing, Zhou Xin, Lu Na. Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data. Mechanical Systems and Signal Processing, 72-73: 303-315, 2016 (SCI WOS:000369196200017, IF: 4.525)

[22] Lu Na, Miao Hongyu. Structure constrained nonnegative matrix factorization for pattern clustering and classification. Neurocomputing, 171: 400-411, 2016 (SCI WOS: 000364883900041, IF: 3.317).

[23] Lu Na, Wu Yidan. Clustering of tree-structured data. IEEE International Conference on Information and Automation, 2015: 1210-1215. (EI: 20161102093088)

[24] Lu Na*, Yin Tao. Motor imagery classification via combinatory decomposition of ERP and ERSP using sparse nonnegative matrix factorization. Journal of Neuroscience Methods, 2015, 249: 41-49 (SCI WOS: 000356555300006, IF: 2.426).

[25] Lu Na*, Li Tengfei, Pan Jinjin, Ren Xiaodong, Feng Zuren, Miao Hongyu. Structure constrained semi-nonnegative matrix factorization for EEG-based motor imagery classification. Computers in Biology and Medicine, 2015, 60: 32-39. (SCI WOS:000353737400003, IF: 1.953)

[26] Lu Na*, Luo Jing. Gradient guided feature selection in stereo matching. International Conference on Electronics, Communications and Networks (CECNet), 2014, (EI: 20161102097579)

[27] Luo Jing, Feng Zuren, Lu Na*. Window adaptive cost aggregation method for stereo correspondence. International Conference on Electronics, Communications and Networks (CECNet), 2014, (EI)

[28] Yang Dewei, Feng  Zuren, Ren Xiaodong, Lu Na. A novel power line inspection robot with dual-parallelogram architecture and its vibration suppression controlAdvanced Robotics, 28(12): 807-819, 2014. (SCI WOS:000337541400001, IF: 0.636)

[29] Lu Na*, Miao Hongyu. Featured circular profile for vessel thresholding. 6th International Congress on Image and Signal Processing (CISP), IEEE, 2013: 437-442.  (EI: 20141117463614)

[30] Lu Na, Silva Jharon, Gu Yu, Gerber, Scott, Wu Hulin, Gelbard Harris, Dewhurst Stephen, Miao Hongyu*. Directional histogram ratio at random probes: a local thresholding criterion for capillary images. Pattern Recognition, 46(7), 1933-1948, 2013 (SCI WOS:000317886600019, EI: 20131316148912, IF: 4.991)

[31] Lu Na*, Feng Zuren. Centroid iteration algorithm for image tracking. Pattern Analysis and Applications, 15(2), 163-174, 2012 (SCI WOS:000303384000006, EI: 20080211012987, IF: 1.352 )

[32] Xu Jintao, Feng Zuren, Lu Na. Optical Flow Estimation with Parameterized Data Term and Warping. Proceedings of the 10th World Congress on Intelligent Control and Automation (WCICA), 4633-4637, Beijing, 2012 (EI: 20130415919833)

[33] 吕娜*, 冯祖仁. 自适应多分辨图像跟踪算法. 计算机研究与发展, 49(8): 1708-1714, 2012 (EI: 20124115554751) 

[34] 吕娜*, 冯祖仁. 一种随机角点检测算法. 模式识别与人工智能, 24(2): 291-298, 2011 (EI: 20112314043782 )

[35] Na Lu*, Zuren Feng. Mathematical model of blob matching and modified bhattacharyya coefficient. Image and Vision Computing, 2008, 26(10): 1421–1434. SCI WOS:000259330700010,  EI: 20083411469438, IF: 2.384

[36] Na Lu*, Zuren Feng. Accumulative intersection space based corner detection algorithm. International Journal of Pattern Recognition and Artificial Intelligence, 2008, 22(8): 15591586. SCI WOS:000262598700005EI: 20090511879909, IF:0.558

[37] Zuren Feng, Na Lu, Ping Jiang. Posterior probability measure for image matching. Pattern Recognition, 2008, 41(7): 2422–2433. SCI WOS:000255818900026EI: 20081511194522, IF: 3.613

[38] 吕娜,冯祖仁非线性交互粒子滤波算法控制与决策, 2007, 22(4): 378–383. EI: 20072210627963

[39] 吕娜,冯祖仁质心迭代图像跟踪算法西安交通大学学报, 2007, 41(12): 1396–1400. EI: 20080211012987

[40] 冯祖仁,吕娜,李良福基于最大后验概率的图像匹配相似性指标研究自动化学报, 2007, 33(1): 18. EI: 20071310513852

[41] Na Lu, Zuren Feng. Numerical potential field and ant colony optimization based path planning in dynamic environment. Proceedings of the 6th World Congress on Intelligent Control and Automation, June 21–23, 2006, Dalian, China. EI: 20071510544254

授权及申请专利:

[1]     吕娜, 井雪. 一种基于深度学习的运动想象脑电信号分类方法. 申请号:201811603323.4

[2]     吕娜, 史夏豪. 一种基于深度学习的火灾图像识别方法. 申请号:201811271332.8

[3]     冯祖仁, 吕娜. 一种基于背景抑制的后验概率图像跟踪方法. 专利号: ZL 2008 1 0018348.8

科研项目:

1.        横向课题:综合通信系统,2019-2022,主持人

2.        科技创新2030“新一代人工智能”重大项目(2018AAA0101500),人在回路的大电网调控混合增强智能基础理论, 2019-2023,子课题负责人

3.        国家重点研发计划“智能机器人”重点专项(2018YFB1306100):工业机器人智能故障诊断及健康评估系统,2019-2022,子课题负责人

4.        国家自然科学基金(61876147):基于运动想象脑电信号的多主体多任务异步实时脑控系统研究,2019-2022,主持人

5.        智能机器人与系统高精尖创新中心开放基金(2016IRS19):基于先验深度学习的脑控机器人研究,2017-2018,主持人

6.        国家自然科学基金(61673312):统计结构学习方法及其在个体差异脑信号分析中的应用研究,2017,主持人

7.        中央高校基本科研业务费专项资金资助, 西安交通大学校内科研基金(国际合作类): 结构学习方法及其在高维复杂数据分析中的应用研究,2015-2017,主持人

8.        国家自然科学基金 61105034):交互协作特征选择方法及其在立体视觉中的应用研究,2012-2014,主持人

9.        教育部博士点基金(20100201120040):基于多特征联盟的无线传感网目标检测定位研究,2011-2013,主持人

10.    第四十九批博士后科学基金(20110491662):鲁棒目标跟踪方法关键技术研究,2011-2014,主持人

11.    中国博士后科学基金第五批特别资助(2012T50805):基于圆形统计学的图像特征分析研究,2012-2015,主持人

12.    中央高校基本科研业务费专项资金资助, 西安交通大学校内科研基金(自然科学类): 基于无线传感网的多节点协同目标检测定位, 2010-2011,主持人

13.    机械制造系统工程国家重点实验室开放课题, 结构学习方法研究, 2015-2016, 主持人

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