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个人简介

李君宝,博士、长聘教授、博士生导师,教育部新世纪人才计划。1978年出生于黑龙江省密山市,2008年博士毕业于哈尔滨工业大学后留校任教,任讲师、副教授、教授、博士生导师。研究方向为机器学习算法、嵌入式智能系统、图像处理。主持国家自然基金、部委重点项目等各类科研课题50余项。发表论文140余篇,其中SCI期刊论文90余篇,中英文专著2部,发明专利11项。担任国家自然基金等多项基金项目评阅人,4个国际期刊副主编。2010年入选哈尔滨工业大学985青年学者支持计划,2012年入选哈尔滨工业大学基础研究杰出人才培育计划,2013年入选教育部“新世纪”优秀人才支持计划,2017获得黑龙江省优秀科技工作者称号。2015年第一完成人获得黑龙江省自然科学二等奖,2021年第一完成人获得黑龙江省高校科技二等奖,2019年入选黑龙江省首批“头雁计划”团队支持计划。 荣誉称号 2010年 哈尔滨工业大学985青年学者支持计划 2012年 哈尔滨工业大学基础研究杰出人才培育计划 2017年 黑龙江省第七届优秀科技工作者 2019年 黑龙江省首批“头雁计划”团队支持计划 工作经历 2008.07-2011.09 哈尔滨工业大学 讲师 2008.09-2011.06 哈尔滨工业大学 博士后 2011.04-2018.11 哈尔滨工业大学 硕导 2011.10-2017.12 哈尔滨工业大学 副教授 2014.04-2018.11 哈尔滨工业大学 博导 2018.01-至今 哈尔滨工业大学 教 授/长聘教授 教育经历 1998.09- 2008.07 哈尔滨工业大学 电气学院 本科 2002.09- 2004.07 哈尔滨工业大学 航天学院 硕士研究生 2004.09- 2008.07 哈尔滨工业大学 电气学院 博士研究生 主要任职 Associate Editor, Journal of Information Hiding and Multimedia Signal Processing Secretary, IEEE IM Beijing&Harbin Joint Chapter Reviewers, Information Sciences, IEEE Trans. on SMC-Part B, Chinese Optics Letter, Signal Processing, Acta Astronautica, Neural Computing & Applications Publication Chair, Second International Conference on Pervasive Computing, Signal Processing and Applications (PCSPA 2011), International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC) 2011/2012 Program committee member, ISSCAA2010, IIHMSP09, ICICIC08 Guest Editor, International Journal of Advancements in Computing Technology 国家自然基金、黑龙江省自然科学基金、河北省自然科学基金等基金项目评阅人

研究领域

研究方向:机器学习算法、嵌入式智能系统、图像处理 课题组隶属于计算学部信息对抗研究所,同时也是作为哈工大人工智能研究院成员单位,黑龙江省首批“头雁计划”支持,一直从事深度学习、强化学习及图像识别技术、基于人工智能的网络空间安全技术及应用的研究工作,开发了基于深度学习的柔性视觉检测系统、基于知识图谱的网络空间敏感信息挖掘、对地可见光探测数据分析处理软件平台、图像深度学习目标识别软件工具、深度学习智能视频分析系统、基于深度学习目标识别等多个应用系统。 方向1. 机器学习算法研究:面向各领域的人工智能系统应用,开展机器学习算法研究工作,重点研究深度学习算法、强化学习算法、图像识别算法的研究,实现面向应用的算法设计、优化及实现,为实现人工智能系统应用提供关键算法支撑。面向各类平台搭载的图像识别应用需求,开展目标检测、识别及跟踪的关键方法、技术及装备研究,突破了适用于特定图像目标分析任务的机器学习建模、嵌入式硬件计算、应用系统优化等关键技术。 方向2:嵌入式智能系统研究:面向功耗体积计算资源受限下人工智能系统应用需求,研究基于DSP/ARM/FPGA平台人工智能技术,突破轻量化识别网络构建及优化、硬件加速计算等,目前已经开发了基于深度学习的柔性视觉检测系统、对地可见光探测数据分析处理软件平台、遥感图像深度学习目标识别软件工具、车载对空红外小目标识别系统、深度学习智能视频分析系统、基于深度学习空中目标识别等多个应用系统。 方向3:基于机器学习的网络空间安全研究:采用机器学习算法实现对网络空间的敏感信息挖掘、网络数据异常检测、网络异常行为分析,提出了网络空间安全分析学习算法,开发了基于知识图谱的网络空间多模态敏感信息安全分析平台,平台已用于实际取得了良好的网络空间安全提升效果。

近期论文

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Wu Ran, Liu Huanyu, Li Junbao. ADCL: Adversarial Distilled Contrastive Learning on lightweight models for self-supervised image classification. Knowledge-Based Systems. (SCI, IF: 8.8), 278: 110824. (2023) (学生一作). Xiaomin Liu, Donghua Yuan, Kai Xue, Jun-bao Li, Huaqi Zhao, Huanyu Liu & Tingting Wang. Diffeomorphic matching with multiscale kernels based on sparse parameterization for cross-view target detection. Applied Intelligence. (SCI, IF: 5.3), 53(8): 9689-9707. (2023) (学生一作). Liu Xiaodong, Guo Haipeng, Liu Huanyu, Li Junbao. Domain migration representation learning for blind magnetic resonance image super-resolution. Biomedical Signal Processing and Control. (SCI, IF: 5.1). 86: 105357(2023) (学生二作). Liu Huanyu, Guo Haipeng, Liu Xiaodong. UHA‐CycleGAN: Unpaired hybrid attention network based on CycleGAN for terahertz image super‐resolution. IET Image Processing. (SCI, IF: 2.3). 17, 2547–2559 (2023) (学生二作). Yuanyuan Sheng, Huanyu Liu, Junbao Li. Bearing performance degradation assessment and remaining useful life prediction based on data-driven and physical model. Measurement Science and Technology. (SCI, IF: 2.4). 34(5): 055002. (2023) (学生一作). Yuanyuan Sheng, Huanyu Liu, Lu Li, Junbao Li. A hybrid method of frequency-weighted energy operator and power spectrum fusion to detect bearing faults. Review of Scientific Instruments. (SCI, IF: 1.6). 94(5): 055102. (2023) (学生一作). Luyin Xiao, Yongjun Xie, Junbao Li, Peiyu Wu. Near-Field Gain Expression for Tapered Circular Aperture Antenna. IEEE Transactions on Antennas and Propagation. (SCI, IF: 5.7). 17(9): 7684-7689. (2023) (学生一作). Zhongjie Zhuang, Jeng-ShyangPan, Junbao Li, Shu-Chuan Chu. Parallel binary arithmetic optimization algorithm and its application for feature selection. Knowledge-Based Systems. (SCI, IF: 8.8). 275: 110640. (2023) (学生一作). Tingting Wang, Huanyu Liu, Junbao Li. Spectral-Spatial Classification of Few Shot Hyperspectral Image With Deep 3-D Convolutional Random Fourier Features Network. IEEE Trans. Geosci. Remote. Sens. (SCI,IF: 8.125) 60: 1-18 (2022) (学生一作) Ran Wu, Huanyu Liu, Jun-Bao Li. Adaptive gradients and weight projection based on quantized neural networks for efficient image classification. Computer Vision and Image Understanding (2022)(SCI,IF:4.886) (学生一作) Xiaomin Liu, Donghua Yuan, Kai Xue, Jun-Bao Li, Huaqi Zhao, Huanyu Liu, Tingting Wang. Diffeomorphic Matching With Multiscale Kernels Based on Sparse Parameterization for Crossing-view Target Detection. Applied Intelligence (2022) (SCI,IF:5.086)(学生一作) Gao Lina, Liu, Bing, Ping Fu, Xu, Mingzhu, Junbao Li ,Visual tracking via dynamic saliency discriminative correlation filter. APPLIED INTELLIGENCE. (SCI,IF: 5.019) 2022.(学生一作) Xu Mingzhu, Ping Fu, Bing Liu, Hongtao Yin, Junbao Li, A novel dynamic graph evolution network for salient object detection . APPLIED INTELLIGENCE. (SCI,IF: 5.019) 2022. (学生一作) Liu Xiaomin, Yuan Donghua, Xue Kai, Junbao Li, Zhao Huaqi, Liu Huanyu, Wang Tingting Diffeomorphic matching with multiscale kernels based on sparse parameterization for cross-view target detection. APPLIED INTELLIGENCE. (SCI,IF: 5.019) 2022.(学生一作) Xiao Luyin, Xie Yongjun, Gao Shida, Junbao Li, Wu Peiyu. Generalized Radar Range Equation Applied to the Whole Field Region. SENSORS (SCI,IF: 3.847) 2022,22(12) . (学生一作) Liu Huanyu, Liu Jiaqi, Li Junbao, Pan Jeng-Shyang, Yu Xiaqiong. DL-MRI: A Unified Framework of Deep Learning-Based MRI Super Resolution[J]. Journal of Healthcare Engineering. 2021.(IF:2.682)(学生一作) Liu Huanyu, Liu Jiaqi, Li Junbao, Pan Jeng-Shyang, Yu Xiaqiong. PSR: Unified Framework of Parameter-Learning Based MR Image Super-Resolution[J]. Journal of Healthcare Engineering. 2021.(IF:2.682)(学生一作) Liu Huanyu, Shao Mingmei, Pan Jeng-Shyang, Li junbao. Multiple Optimizations-Based ESRFBN Super-Resolution Network Algorithm for MR Images. Applied Sciences, 2021.(SCI,IF=2.679)(学生一作) Huanyu Liu, Qing Luo Mingmei Shao, Jeng-Shyang Pan, and Junbao Li. Joint Channel Pruning and Quantization-based CNN Network Learning with Mobile Computing-based Image Recognition. Wireless Communications and Mobile Computing, 2021.(SCI,IF=2.336)(学生一作) Wang T, Xu L, Li J. SDCRKL-GP: Scalable deep convolutional random kernel learning in gaussian process for image recognition[J]. Neurocomputing, 2021, 456: 288-298.(IF:5.719)(学生一作) Ran Wu,Xinmin Guo,Jian Du, Junbao Li. Accelerating Neural Network Inference on FPGA-Based Platforms—A Survey. Electronics, 2021.(SCI, IF= 2.397)(学生一作) Xu, Mingzhu; Fu, Ping; Liu, Bing; Li, Junbao ; Multi-Stream Attention-Aware Graph Convolution Network for Video Salient Object Detection, IEEE Transactions on Image Processing, 2021, 30:4183-4197. (学生一作) Xiao Luyin, Xie Yongjun, Wu Peiyu, Junbao Li. Near-Field Gain Expression for Aperture Antenna and Its Application. IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS , 2021,20(7):1225-1229 (SCI, IF= 3.825) (学生一作) Liu Huanyu, Liu Jiaqi, Junbao Li, Pan Jeng-Shyang, Yu Xiaqiong PSR: Unified Framework of Parameter-Learning-Based MR Image Superresolution. JOURNAL OF HEALTHCARE ENGINEERING. 2021, (SCI, IF= 3.822) (学生一作) Chu Shu-Chuan, Zhuang, Zhongjie, Junbao Li, Pan, Jeng-Shyang A Novel Binary QUasi-Affine TRansformation Evolutionary (QUATRE) Algorithm . APPLIED SCIENCES-BASEL 2021,11(5) (SCI, IF= 2.838) Liu Xiaomin, Junbao Li, Pan Jeng-Shyang, Wang Shuo. An advanced gradient texture feature descriptor based on phase information for infrared and visible image matching. MULTIMEDIA TOOLS AND APPLICATIONS, 2021, (SCI, IF=2.577) (学生一作) Pan, Jeng-Shyang, Tian, Ai-Qing, Chu, Shu-Chuan, Junbao Li. Improved binary pigeon-inspired optimization and its application for feature selection. APPLIED INTELLIGENCE 2021,51(12):8661-8679(SCI, IF=5.019) Xiaomin Liu, Jun-Bao Li , Jeng-Shyang Pan, et al. Image-Matching Framework Based on Region Partitioning for Target Image Location. Telecommunication Systems, 2020, DOI : 10.1007/s11235-020-00657-x. (SCI, IF=2.314) (学生一作) Tingting Wang, Huayou Su, Jun-Bao Li , DWS-MKL: Depth-width-scaling multiple kernel learning for data classification. Neurocomputing, 2020, 441, 455-467. (SCI, IF=5.719)(学生一作) Tingting Wang, Bo Dong, Kaichun Zhang, Junbao Li, Lei Xu. Slim-RFFNet: Slim deep convolution random Fourier feature network for image classification. Knowledge-Based Systems, (2022) 107878-107890(SCI,IF:8.038).(学生一作) Xiuyuan Chen, Xiyuan Peng, Jun-Bao Li , Chaoying Huo. Sparse Autoencoder Based Manifold Analyzer Model of Multi-Angle Target Feature. IEEE ACCESS. 2020, 8: 153250 - 153263 . DOI: 10.1109/ACCESS.2020.3017919. (SCI, IF=3.745) (学生一作) Xu Mingzhu, Bing Liu, Ping Fu, Junbao Li, Hu Yuhen, Feng Shou. Video Salient Object Detection via Robust Seeds Extraction and Multi-Graphs Manifold Propagation IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2020,30(7): 2191-2206. (SCI, IF=4.685) (学生一作) Wang, Shuo, Lv, Xudong, Junbao Li, Ye, Dong. Coarse Semantic-Based Motion Removal for Robust Mapping in Dynamic Environments. IEEE ACCESS, 2020,8:74048-74064(SCI, IF=3.367) (学生一作) Xiaomin Liu, Jun-Bao Li , and Jeng-Shyang Pan. Feature point matching based on distinct wavelength phase congruency and log-Gabor filters in infrared and visible images. Sensors. 2019. (SCI, IF=3.031)(学生一作) Yifan Li, Junbao Li, Jeng-Shyang Pan. Hyperspectral Image Recognition Using SVM Combined Deep Learning. Journal of Internet Technology Volume 20 (2019) No.3, 851-859. (SCI, IF:1.005). (学生一作) Xu Mingzhu; Liu Bing; Fu Ping; Li Junbao; Hu Yuhen. Video Saliency Detection via Graph Clustering With Motion Energy and Spatiotemporal Objectness, IEEE Transactions on Multimedia, 2019, 21(11): 2790-2805.(学生一作) Wu Ruidong, Bing Liu, Fu Jiafeng, Xu Mingzhu, Ping Fu, Junbao Li. Research and Implementation of epsilon-SVR Training Method Based on FPGA.ELECTRONICS 2019,8(9) :919-929. (SCI, IF:2.690) (学生一作) Bing Liu, Zou Danyin, Lei Feng, Ping Fu, Junbao Li. An FPGA-Based CNN Accelerator Integrating Depthwise Separable Convolution. ELECTRONICS, 2019,8(3): 281-288. (SCI, IF:2.690) Wu Ruidong, Bing Liu, Ping Fu, Junbao Li, Feng Shou.An Accelerator Architecture of Changeable-Dimension Matrix Computing Method for SVM, ELECTRONICS, 2019,8(2) :143 -153. (SCI, IF: 2.690) (学生一作) Jun-Bao Li, Huanyu Liu, Jeng-Shyang Pan, Hongxun Yao. Training Samples-Optimizing Based Dictionary Learning Algorithm for MR Sparse Superresolution Reconstruction. Biomedical Signal Processing and Control. 2018, 39:177-184 (IF: 3.137) Cui Zheng, Jingli Yang, Shouda Jiang, Junbao Li, Lin Lianlei, Gu Yanfeng. An infrared-small-target detection method in compressed sensing domain based on local segment contrast measure. INFRARED PHYSICS & TECHNOLOGY, 2018, 93: 41-52. (SCI, IF:2.997)(学生一作) Cui Zheng, Jingli Yang, Shouda Jiang, Junbao Li, Gu Yanfeng. Robust spatio-temporal context for infrared target tracking, INFRARED PHYSICS & TECHNOLOGY,2018,91:263-277. (SCI, IF: 2.997) (学生一作) Li Li, Chao Sun, Lin Lianlei, Junbao Li, Shouda Jiang, Yin, Jingwei.A dual-kernel spectral-spatial classification approach for hyperspectral images based on Mahalanobis distance metric learning. INFORMATION SCIENCES, 2018,429:260-283.(SCI, IF:8.233) (学生一作) Li Li, Chao Sun, Lin Lianlei, Junbao Li, Shouda Jiang. A Mahalanobis metric learning-based polynomial kernel for classification of hyperspectral images. NEURAL COMPUTING & APPLICATIONS,2018,29(4):1103-1113.(SCI, IF:5.102) (学生一作) Shi Zhen, Changan Wei, Junbao Li, Ping Fu, Shouda Jiang Hierarchical search strategy in particle filter framework to track infrared target. NEURAL COMPUTING & APPLICATIONS, 2018,29(2):469-481.(SCI, IF:5.102) (学生一作) Jun-Bao Li, Jing Liu, Jeng-Shyang Pan, Hongxun Yao. Magnetic Resonance Super-resolution Imaging Measurement with Dictionary-optimized Sparse Learning. MEASUREMENT SCIENCE REVIEW, 17 , (2017), No. 3, 145-152.( IF:1.319) Jun-Bao Li, Jeng-Shyang Pan. Multiple sensors-based kernel machine learning in smart environment. Review of Scientific Instruments 88, 015006 (2017); http://doi.org/10.1063/1.4973563(IF:1.587) Jun-Bao Li, Xiaodan Xie, Jia Zhai, Jeng-Shyang Pan. Hyperspectral sensing data analysis based on quasiconformal mapping-based multiple kernels learning machine. Review of Scientific Instruments 88, 065004 (2017).(IF:1.587) Xiuyuan Chen, Xiyuan Peng, Ran Duan, and Junbao Li. Deep kernel learning method for SAR image target recognition. Review of Scientific Instruments 88, 104706 (2017). https://doi.org/10.1063/1.4993064. (IF:1.587)(学生一作) Qinghua Luo, Yu Peng, Junbao Li, Xiyuan Peng.MWPCA-ICURD: Density-based Uncertain Clustering Method Discovering Specific Shape Original Features in Sensor Networks. Sensor, 2017. (IF:3.031) (学生一作)

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