北京航空航天大学导师教师信息介绍简介-张宝昌

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个人简历

特聘研究员，2018年进入北航长聘系列，长期从事复杂背景下快速小目标检测与识别研究。
证明了混合高斯波函数的不确定性上界，发表在顶刊IJCV(领域第一11.54)；提出局部模式构建的一系列的原创模型。
入选教育部新世纪优秀人才计划、深圳市孔雀团队海外人才计划，获中国电子学会奖2项，陕西省自然科学奖一等1项（排名第二）。
最佳会议论文4篇，单篇SCI最高引用500次，HGPP和LDP被称为里程碑算法（2篇论文引用超过1500次），SCI高引论文6篇。发表CVPR、ICCV、NeurPS、AAAI、IJCAI以及IEEE汇刊等顶会、顶刊60余篇。相关工作源代码关注 https://github.com/bczhangbczhang/ 。
担任了多个知名SCI期刊的首席客座主编或者客座主编。担任Q2 sensor期刊编委，SCI期刊IJARS副主编。顶会CVPR、ICCV、ACMMM的程序委员会成员。培养校级、院级优秀论文共6人。培养学生逐渐成为国家栋梁，工作单位包括国家税务总局，社科院，航天院所，德国波恩大学留学。
研究成果1：提出多高斯不确定性理论。国际上首次证明混合高斯波函数的不确定性上界，是经典理论的一般性扩展。相关论文一作发表于视觉领域顶刊IJCV，2016年大陆学者一作正刊仅有6篇。
学术成果2；独立提出调制卷积神经网络，在深度模型压缩方面理论与工程实现处于领先位置；在1-bit深度模型压缩方面在大型数据集合上取得世界上最好的性能，并进行推广。
学术成果3：提出深度协同端的计算框架，基于AI芯片构建了相关的软硬件系统，在工业界进行成果转化。相关工作长文发表顶刊Automatica。
http://dblp.uni-trier.de/pers/hd/z/Zhang:Baochang.html
https://github.com/bczhangbczhang/

教育经历

[1] 哈尔滨工业大学 | 计算机科学与技术本硕博

工作经历

社会兼职

[1]2019.6-2020.6
百度深度学习实验室学术顾问
Academic Advisor of Institute of Deep Learning, Baidu Research

研究方向

[1] 神经网络结构搜索，尤其关注功耗约束、通讯带宽约束的网络结构设计

[2] 深度学习模型压缩；视觉目标检测与识别，尤其关注小目标感知；视频识别；机器学习理论与应用

联系方式

[1]Email：

研究领域

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深度学习模型压缩；视觉目标检测与识别，尤其关注小目标感知；视频识别；机器学习理论与应用
神经网络结构搜索，尤其关注功耗约束、通讯带宽约束的网络结构设计
Research interest: Pattern Recognition, Machine Learning, Face Recognition, Wavelets
http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/z/Zhang:Baochang.html

开授课程

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[1]图像处理系列实验
[2]Computer fundmental and computer vision
[3]大数据与类脑智能
[4]机器学习理论与应用

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科研项目

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[1] [23]CO-PI: Few-shot Learning for Automatic Modulation Classification in Unmanned Systems, 2018-2019. 380,000/1,000,000RMB
[2] [22]CO-PI: The fusion for heterogeneous data for UAV security, 180,000/1,200,000 RMB, Key project of NSFC.
[3] [21]CO-PI:Pedestriandetectionbasedontopologicalmodelling,NSFC, 420,000/840,000 RMB
[4] [20]Co-PI: Bionic-Robot Design and Applications, Shenzhen Peacock Plan 2017-2022. I am in charge of SLAM on TX2 and AI Chips. 4,000,000/20,000,000 RBM
[5] [19]PI: Fast H.264 video decoder and video surveillance algorithms, industry, 100,000 RMB.
[6] [18]PI:Development on Key Technologies of Visual Positioning and Navigation, Industry, 150,000 RMB
[7] [17]PI:3D Path planning for UAVs, 50,000 RMB
[8] [16]PI: Renminbi serial number recognition, Industry, 80,000 RMB
[9] [15]PI: Highly Efficient Gesture recognition for UAV controlling, Industry, 380,000 RMB
[10] [14]PI: Fast ship detection based on deep learning, Industry 170,000 RMB
[11] [13]PI: Biometric systems (Keystroke, Palmprint and face recognition), Industry, 220,000 RMB
[12] [12]PI: Weakly-supervised X-Ray object detection, Industry, 300,000 RMB
[13] [11]PI: Beihang Fund for Young Talent, 2018-2010. 1,200,000 RMB
[14] [10]PI: VINS-MONO on AI Chips, Industry, 430,000 RMB.
[15] [9]Co-PI:CrowdcountingandmotionpredictionsystembasedUAVs, 400,000/1,000,000 RMB
[16] [8]PI: Deep RNNs for railway signal processing 60,000RMB
[17] [7]PI: Deep learning for Radar signal processing, 350,000RMB
[18] [6]PI: Highly efficient bus surveillance system, 440,000 RMB
[19] [5]PI: Deep Compression Models (Modulated convolutional networks, MCNs) for Small Object detection and Tracking in very High-resolution images, Industry. 980,000RMB/ MCNs(500,000RMB for CVPR paper) Applications (480,000RMB)
[20] [4]PI: Program for New Century Excellent Talents in University of Ministry of Education of China, 2014-2016, 500,000 RMB

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论文

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[1] Z. Han, J. Jiao, B. Zhang, Q. Ye, Visual object tracking via sample-based Adaptive Sparse Representation (AdaSR), Pattern recognition, 2011.( SCI) (IF=4.582)
[2] R. Xu, J. Jiao, B. Zhang, pedestrian detection from images based on Cascaded L1-norm minimization learning, Pattern recognition, 2012.( SCI) (IF=4.582)
[3] Jie Xu, Yuan Yan Tang, Bin Zou, Zongben Xu, Luoqing Li, Yang Lu, Baochang Zhang: The Generalization Ability of SVM Classification Based on Markov Sampling. IEEE Transactions cybernetics 45(6): 1169-1179 (2015) (SCI) (IF=7.384)
[4] B. Zhang, Y. Gao, S. Zhao and B. Zhong, “Kernel Similarity Modeling of Texture Pattern Flow for Motion Detection in Complex Background”, IEEE Transactions on Circuits and Systems for Video Technology, 2010. (SCI) (IF=3.599)
[5] Lei Wang, Baochang Zhang*, Wankou Yang:Boosting-Like Deep Convolutional Network for Pedestrian Detection. Signal processing and image communication, 2016. (SCI) (IF=2.244)
[6] Changqing Zou, Tianfan Xue, Xiaojiang Peng, Honghua Li, Baochang Zhang*, Ping Tan,Jianzhuang Liu:An example-based approach to 3D man-made object reconstruction from line drawings. Pattern Recognition 60: 543-553 (2016) (SCI) (IF=4.582)
[7] Baochang Zhang, Z. Li, X. Cao, Qixiang Ye, C. Chen, L. Shen, A. Perina, and R. Ji,"Output Constraint Transfer for Kernelized Correlation Filter in Tracking," IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2018, Digital Object Identifier 10.1109/TSMC.2016.**. (SCI)
[8] Chunlei Liu, Wenrui Ding, Xiaodi Wang, Baochang Zhang: Hybrid Gabor Convolutional Networks. Pattern Recognition Letters 116: 164-169 (2018)
[9] Baochang Zhang, Zhigang Li, Alessandro Perina, Alessio Del Bue, Vittorio Murino: Adaptive Local Movement Modelling for Object Tracking. IEEE Transactions on Circuits and Systems for Video Technology. 2017. (IF=3.599)
[10] Juning Liu, Xianbin Cao, Yan Li, Baochang Zhang, Online Multi-Object Tracking Using Hierarchical Constraints for Complex Scenarios, IEEE Transactions on Intelligent Transportation Systems, 2017. SCI IF=3.72.
[11] Shuman Tian, Xianbin Cao, Yan Li, Xiantong Zhen, Baochang Zhang, Glance and Stare: Trapping Flying Birds in Aerial Videos by Adaptive Deep Spatio-Temporal Features, IEEE Trans. on Circuits and Systems for Video Technology. 2017. (IF=3.599)
[12] Baochang Zhang, Shang Zhen Luan, Chen Chen, Jungong Han, Ling Shao, Latent Constrained Correlation Filter，IEEE Transactions on Image Processing, 2017. (IF=5.071) Highly Cited Papers
[13] Baochang Zhang, Yun Yang, Chen Chen, Jungong Han, Ling Shao, Action Recognition Using 3D Histograms of Texture and A Multi-class Boosting Classifier, IEEE Transactions on Image Processing, 26(10) ,2017. (IF=5.071) Highly Cited Papers
[14] Baochang Zhang, A. Perina, Ce Li, Q. Ye, Vittorio Murio, A. del bue, Manifold constraint transfer for visual structure-driven optimization, Pattern Recognition, 2018. (IF=4.582)
[15] Ce Li, Chunyu Xie, Baochang Zhang*, Chen Chen, Jungong Han. Deep Fisher discriminant learning for mobile hand gesture recognition, Pattern Recognition, 2018.
[16] L. Yang, Ce Li, J. Han, C. Chen, Q. Ye, Baochang Zhang*, Xianbin Cao, Wanquan Liu, Manifold Constrained Convolutional Sparse Coding for Image Sets, IEEE Journal of Selected Topics in Signal Processing, 2017. (IF=5.3).
[17] Linlin Yang, Ce Li, Chunyu Xie, Linna Wang, Baochang Zhang:Adaptive multiclass correlation filters and its applications in the time series recognition. J. Electronic Imaging 27(03): 033010 (2018)
[18] Jiewan Zheng, Xianbin Cao, Baochang Zhang, Xiantong Zheng, Deep Ensemble Machine for Video Classi?cation, IEEE Trans. Neural Network and Learning System. 2019.
[19] Baochang Zhang, Jiaxin Gu, Chen Chen, Jungong Han, Xiangbo Su, Jianzhuang Liu, One-Two-One network for Compression Artifacts Reduction in Remote Sensing, ISPRS Journal of Photogrammetry and Remote Sensing, 2018. (IF=6.387). Highly Cited Papers
[20] Shangzhen Luan, Chen Chen, Baochang Zhang, Jungong Han, Jianzhuang Liu: Gabor Convolutional Networks. IEEE Trans. Image Processing 27(9): 4357-4366 (2018) Highly Cited Papers

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荣誉及奖励

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[1]教育部新世纪优秀人才计划

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