1. Xu Niu, Na Lu*, Ruofan Yan, and Huan Luo. A time-frequency map generation network embedded with spectral self-attention for motor imagery classification, Biomedical Signal Processing and Control, vol. 93, p. 106206, 2024, doi: https://doi.org/10.1016/j.bspc.2024.106206. (SCI, IF: 5.1)
2. Hanxuan Wang, Na Lu*, Huan Luo, Qinyang Liu. Self-supervised clustering with assistance from off-the-shelf classifier. Pattern Recognition, Accepted, 2023. (SCI, IF: 8.518)
3. Zhiyan Cui, Na Lu*. Feature-comparison network for visual tracking. Applied Intelligence, Accepted, 2023. (SCI, IF: 5.08)
4. Na Lu*, Zhiyan Cui, Huiyang Hu and Tao Yin. Multi-view and multi-level network for fault diagnosis accommodating feature transferability. Expert Systems with Applications, 213: 19057, 2023. (SCI, IF: 8.665)
5. Tao Yin, Na Lu*, Guangshuai Guo, Yaguo Lei, Shuhui Wang, Xiaohong Guan. Knowledge and data dual-driven transfer network for industrial robot fault diagnosis. Mechanical Systems and Signal Processing, 182: 109597, 2023. (SCI, IF: 8.934)
6. Huan Luo, Na Lu*, Xu Niu, Xuecai Zhou. Synthetic feature generative adversarial network for motor imagery classification: create feature from sampled data. Chinese Conference on Biometric Recognition, 324-331, 2022. (EI: 20225213295734)
7. Ruofan Yan, Na Lu*, Xu Niu, Yuxuan Yan. Hemispheric asymmetry measurement network for emotion classification. Chinese Conference on Biometric Recognition, 307-314, 2022. (EI: 20225213295732 )
8. Jianghong Kang, Na Lu*, Xu Niu. Incremental EEG biometric recognition based on EEG relation network. Chinese Conference on Biometric Recognition, 424-432, 2022. (EI: 20225213295745)
9. Zhiyan Cui, Na Lu*, Qian Wang*, Jingjing Guo, Jiaming Yang. Multiple object tracking based on tracking compensation for low-resolution scenarios. IEEE International Conference on Image Processing, Computer Vision and Machine Learning, 2022 (ICICML2022).
10. Zhiyan Cui, Na Lu*, Weifeng Wang, Guangshuai Guo. Dual global-aware propagation for few-shot learning. Image and Vison Computing, 128: 104574，2022. (SCI, IF: 3.86)
11. Zhiyan Cui, Qian Wang*, Jingjing Guo, Na Lu*. Few-shot classification of façade defects based on extensible classifier and contrastive learning. Automation in Construction, 141:104381, 2022. (SCI, IF: 10.517)
12. Na Lu*. Dark convolutional neural network for forest smoke detection and localization based on single image. Soft Computing, 26: 8647-8659, 2022. (SCI, IF: 3.643)
13. Zhiyan Cui, Na Lu*, Weifeng Wang. Pseudo loss active learning for deep visual tracking. Pattern Recognition, 130: 108773, 2022. (SCI, IF: 8.518)
14. Xu Niu, Na Lu*, Jianghong Kang, Zhiyan Cui. Knowledge-driven feature component interpretable network for motor imagery classification. Journal of Neural Engineering, 19: 016032, 2022. (SCI MEDLINE: 34942608, IF: 5.379)
15. Na Lu*, Huiyang Hu, Tao Yin, Yaguo Lei, Shuhui Wang. Transfer relation network for fault diagnosis of rotating machinery with small data. IEEE Transactions on Cybernetics, 52(11): 11927-11941, 2022. (SCI, IF: 19.118)
16. Saibo Xing, Yaguo Lei, Bin Yang, Na Lu. Adaptive knowledge transfer by continual weighted updating of filter kernels for few-shot fault diagnosis of machines. IEEE Transactions on Industrial Electronics, 69(2): 1968-1976, 2022. (SCI WOS:000712582800085, IF: 8.236)
17. Saibo Xing, Yaguo Lei, Shuhui Wang, Na Lu, Naipeng Li. A label description space embedded model for zero-shot intelligent diagnosis of mechanical compound faults. Mechanical Systems and Signal Processing, 162: 108036, 2021. (SCI WOS:000674488200002, IF: 8.934)

18. Zhiyan Cui, Na Lu*. Feature selection accelerated convolutional neural networks for visual tracking. Applied Intelligence, 51(11): 8230-8244, 2021. (SCI, IF: 5.08)

19. Jing Luo, Weiwei Shi, Na Lu, Jie Wang et al. Improving the performance of multisubject motor imagery-based BCIs using twin cascaded softmax CNNs. Journal of Neural Engineering, In press. (SCI, IF: 4.141 )

20. Na Lu*, Tao Yin. Transferable common feature space mining for fault diagnosis with imbalanced data. Mechanical Systems and Signal Processing, 156: 107645, 2021. (SCI, IF: 6.471)
21. Bin Yang, Chi-Guhn Lee, Yaguo Lei, Naipeng Li, Na Lu. Deep partial transfer learning network: A method to selectively transfer diagnostic knowledge across related machines. Mechanical Systems and Signal Processing, 156: 107618, 2021. (SCI, IF: 6.471)
22. Jie Wang, Zuren Feng, Xiaodong Ren, Na Lu, Jing Luo, Lei Sun. Feature subset and time segment selection for the classification of EEG data based motor imagery. Biomedical Signal Processing and Control, 61: 102026, 2020. (SCI, IF: 3.063)
23. Hanxuan Wang, Na Lu*. Deep Embedded Clustering with Asymmetric Residual Autoencoder, China Automation Congress, 2020.
24. Tao Yin, Na Lu*. Knowledge Graph Model of Power Grid for Human-machine Mutual Understanding, China Automation Congress, 2020.
25. Na Lu*, Tao Yin . A pipeline of stereo vision based visual odometer for unmanned aerial vehicle , China Automation Congress, 2020.
26. Luo Jing, Gao Xing, Zhu Xiaobei, Wang Bin, Na Lu, Jie Wang. Motor imagery EEG classification based on ensemble support vector learning. Computer Methods and Programs in Biomedicine, 193: 105464, 2020.
27. 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.
28. Lu Na*, Yin Tao, Jing Xue. A Temporal Convolution Network Solution for EEG Motor Imagery Classification. 19^th IEEE International Conference on BioInformatics and BioEngineering, 2019 (Acceptance rate: 33%).
29. 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. 
30. 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)
31. 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)
32. 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, ESI Highly Cited Paper)
33. 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%)
34. 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)
35. 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, 2018，In press (SCI, IF: 5.131)
36.  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, ESI Highly Cited Paper)
37. 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, 46：10-17，2018 (SCI  WOS:000447109800003, IF: 3.063)
38. 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)
39. 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)
40. 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.
41. Lu Na*, Ren Xiaodong, Song Jinbo, Wu Yidan. Visual guided deep learning scheme for fall detection. IEEE Conference on Automation Science and Engineering, 2017
42. 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, IEEE EMBS Best Paper Award, ESI Highly Cited Paper)
43. 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)
44. 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)
45. 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)
46. 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 )
47. 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, ESI Highly Cited Paper)
48. 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).
49. Lu Na, Wu Yidan. Clustering of tree-structured data. IEEE International Conference on Information and Automation, 2015: 1210-1215. (EI: 20161102093088)
50. 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).
51. 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)
52. Lu Na*, Luo Jing. Gradient guided feature selection in stereo matching. International Conference on Electronics, Communications and Networks (CECNet), 2014, (EI: 20161102097579)
53. Luo Jing, Feng Zuren, Lu Na*. Window adaptive cost aggregation method for stereo correspondence. International Conference on Electronics, Communications and Networks (CECNet), 2014, (EI)
54. Yang Dewei, Feng  Zuren, Ren Xiaodong, Lu Na. A novel power line inspection robot with dual-parallelogram architecture and its vibration suppression control，Advanced Robotics, 28(12): 807-819, 2014. (SCI WOS:000337541400001, IF: 0.636)
55. 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)
56. 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)
57. 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 )
58. 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)
59. 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页, 2012 (EI: 20124115554751) 
60. 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页, 2011 (EI: 20112314043782 )
61. 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）
62. Na Lu*, Zuren Feng. Accumulative intersection space based corner detection algorithm. International Journal of Pattern Recognition and Artificial Intelligence, 2008, 22(8): 1559–1586. （SCI WOS:000262598700005，EI: 20090511879909, IF:0.558）
63. Zuren Feng, Na Lu, Ping Jiang. Posterior probability measure for image matching. Pattern Recognition, 2008, 41(7): 2422–2433. （SCI WOS:000255818900026，EI: 20081511194522, IF: 3.613）
64. 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）
65. 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）
66. 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): 1–8. （EI: 20071310513852）
67. 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, 史夏豪. 一种基于深度学习的火灾图像识别方法. 专利号：ZL 201811271332.8
2. 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 200810018348.8
3. 吕娜，胡辉阳. 一种基于迁移关系网络的机械故障诊断方法. 专利号：ZL202010431513.3
4. 吕娜，尹涛，胡辉阳. 一种基于可迁移共特征空间挖掘的故障诊断方法. 专利号：ZL 202011323670.9
5. 吕娜，郭广帅，崔志岩. 一种多视角多层次工业机器人迁移故障诊断方法. 专利号：ZL 202111389808.X
6. 吕娜，于志洋，王臻卓. 一种支持人机双向理解的电网环境模型及建模方法. 申请号：202011225933.2
7. 吕娜，刘星辰. 脑机接口信号分类方法、系统、设备和存储介质. 申请号：2021104218848
8. 吕娜，崔志岩，王玮丰，黄彦浩，裘微江，李文臣. 一种针对视觉跟踪模型的人在回路训练方法及相关装置. 申请号：2021105467142
9. 吕娜，郭广帅，胡辉阳. 一种知识驱动的工业机器人智能迁移故障诊断方法. 申请号：202111139011.4
10. 吕娜，康江宏，王臻卓. 一种脑电身份识别方法及系统. 申请号：202110963479.9
11.  吕娜，于志洋，王晓鹏，王臻卓. 一种人机友好的数据逻辑融合电力知识图谱及其构建方法. 申请号：202111389812.6
12.  吕娜，王晓鹏，郭浩，许富诚. 一种基于知识图谱的自然语言交互软件框架. 申请号：202310638728.6
13.  吕娜，牛旭. 一种低信噪比超短时信号的分类方法及系统，申请号：202311191013.7
14.  吕娜, 王瀚璇, 王子璇. 电力系统暂态稳定可解释评估方法、系统、设备及存储介质. 申请号：202311190271.3
15.  吕娜，罗欢，王淑彤，郭苏逸，徐菁浦. 一种社交认知能力增强系统，软件著作权，已提交

科研项目：

1. 陕西省自然科学基金面上项目（2024JC-YBMS-486），2024-2025，主持
2. 横向课题：综合语音******. 2024-2026, 主持
3. 横向课题：基于对抗学习的******. 2024-2026, 主持
4. 横向课题：航******研究. 2023-2024, 主持
5. 国家重点研发计划（2022YFB3402100）：高端装备协同智能故障诊断理论与预测方法，2022.12-2025.11，项目骨干
6. 国家自然科学基金重点基金（U22B2036）：社交网络行为的异常感知、群体协作与一体化控制研究，2023-2026，项目骨干
7. 基于混合智能的******系统研究，2021-2023
8. 横向课题：综合**系统，2019-2023，主持
9. 陕西省高校教学改革研究项目（重点项目）：基于学科交叉实践创新平台的机器人系列课程与机器人教育实践基地建设，2017-2019，第二参与人
10. 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
11. 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
12. 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
13. 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
14. 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
15. 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
16. 国家自然科学基金（51475355）：内外激励耦合下的复杂齿轮传动系统动态特性与诊断方法研究，2015-2018，骨干成员
17. 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
18. 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
19. 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
20. 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
21. 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
22. 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