教师姓名:石匆
邮箱地址:shicong@cqu.edu.cn
工作电话:未公开

课题组长期诚聘弘深青年教师(助理研究员,有硕导申请资格):

方向1:类脑人工智能模型算法研究

方向2:数字或数模混合集成电路设计

方向3:FPGA开发、嵌入式系统设计

热烈欢迎相关领域的海内外人才加入!具体应聘要求、薪酬待遇(基本待遇为30-40万/年)可参考院校相关政策文件。对入职后成果突出者,课题组将额外奖励15-20万元/年。


石匆,博士,研究员,士生导师

首批重庆“英才计划”青年拔尖人才

庆大学百人计划学者

重庆大学DSC-CPS教育部重点实验室智能感知芯片与系统研究所副所长

国际电气与电子工程师协会(IEEE)会员

中国计算机学会(CCF)会员、CCF-集成电路设计专委会委员

中国图象图形学会(CSIG)会员、CSIG-类脑视觉专委会委员

中国光学工程学会(CSOE)高级会员

中国人工智能学会(CAAI)会员

专业领域:数字芯片集成电路设计,电路与系统,人工智能,类脑计算,图像处理和计算机视觉

1. 联系方式

E-mail:       shicong@cqu.edu.cn

办公地址:  重庆市沙坪坝区沙正街174号重庆大学A区主教学楼2209


2. 教育工作经历

2019.02-至今         重庆大学  微电子与通信工程学院,研究员,博士生导师

2015.02-2018.12    哈佛大学医学院  Schepens视觉科学研究中心,博士后

2009.09-2014.07    清华大学  电子工程系,博士研究生

2009.09-2014.06    中国科学院半导体研究所 超晶格国家重点实验室,博士研究生(教育部高校-中科院联合培养项目)

2003.09-2009.06    哈尔滨工业大学  电子科学与技术系,本科、硕士研究生


3. 招生信息

石匆博士长期从事智能视觉图像处理和人工神经网络芯片电路设计、系统集成及应用算法研究,共发表学术论文50余篇,包括集成电路设计顶级期刊IEEE JSSC和顶级会议ISSCC等。担任IEEE TNNLSIEEE TCSVTIEEE TBioCAS、IEEE TCAS-1IEEE TCAS-2 、IEEE TVLSI、IJCV等人工智能、电路与系统、计算机视觉领域顶级期刊审稿人,2019-2021 IEEE ICTA会议技术程序委员会成员(TPC Member)及其2019、2021年度分会主席,IEEE ASICON会议论文审稿人等。获得8项国内外授权发明专利。

目前研究方向:智能视觉图像处理和类脑深度神经网络算法、数字芯片与系统设计

现招收具有电子或信息类专业基础的博士、硕士研究生。课题项目面向学术前沿,主要涉及图像视频处理、人工智能算法和数字集成电路Verilog设计。课题组具备良好的工作环境,提供优厚的津贴补助、成果奖励及企业赞助奖学金,课题组与哈佛大学、清华大学、中科院等国内外顶尖科研机构具有长期密切交流合作,对直博生和组内硕士提拔深造的博士生确保哈佛大学访学1年机会课题组现有教授/研究员1人,讲师/助理研究员1人,在读博士生4人,在读硕士生11人,本科实习生4人。已毕业硕士生2人。

招生专业

学术型博士: 信息与通信工程 (081000)

学术型硕士: 信息与通信工程 (081000)  

专业型硕士: 电子信息 (085400)

招生说明

1. 对硕士起点的博士招生,需有多媒体信号处理或机器学习的应用背景项目经历,并开发过相应的专用芯片或FPGA系统,本科和硕士期间专业不限。

2. 对保研(含直博)和考研生,本科需为电子信息、电子工程、通信工程、信号处理等专业,欢迎来自这些专业、并有意愿进入国家人才紧缺的IC设计业、从事领域专用(domain-specific)智能芯片开发的同学。


4. 项目经历

1. 面向全仿生视觉芯片的脉冲型神经网络处理器设计. 国家自然科学基金联合基金重点项目子课题,2021-2024,76万,主持

2. 类脑智能超低功耗人脸识别CMOS硅基芯片设计研究. 重庆先锋技术研究院横向项目,2021-2022,200万,主持

3. 可片上深度学习的类脑神经形态芯片设计研究. 重庆市自然科学基金重点项目(省级),2021-202224万,主持

4. 类脑深度脉冲神经网络芯片设计研究. 重庆市留学人员回国创业创新支持计划,2021-2021,5万,主持

5. 高能效类脑深度脉冲神经网络计算芯片设计研究. 中国科学院计算技术研究所计算机体系结构国家重点实验室开放课题,2020-2021,10万,主持

6. 重庆英才计划青年拔尖人才培养基金.  重庆英才计划(省级),2020-2022,40万,主持

7. 神经网络处理器设计. 国家重点研发计划项目子课题,2020-202287万,主持

8. 高能效类脑计算神经网络芯片设计研究. 重庆市自然科学基金重点项目(省级),2019-202180万,主持

9. 重庆大学百人计划科研启动经费. 重庆大学百人计划,2019-2021100万,主持

10. Visual assessment system for retinal function/drug discovery. 美国国立卫生研究院(NIH)项目,2015-201722万美元,主研

11. Wearable collision warning device for blind and visually impaired. 美国国防部(DoD)重点项目,2015-2019300万美元,主研

12. Computer display vision syndrome. 三星公司资助项目,2015-201515万美元,参与

13. Bioptic driving by visually impaired. 美国国立卫生研究院(NIH/NIA)R01重点项目,2012-2018200万美元,参与

14. 基于光电子/微电子混合集成的视觉芯片. 国家自然科学基金重点项目,2013-2017310万,参与

15. 大规模并行图像处理芯片研究. 国家重点基础研究发展(973)计划纳米科技课题,2011-2015732万,主研

16. 超高速CMOS图像传感器芯片的前端设计与芯片测试验证. 02科技重大专项,2011-2014750万,参与


5. 师生动态

[2022-04-02]

祝贺课题组何俊贤同学(2019级博士生)关于混合智能视觉运动感知芯片设计的研究论文Low-Cost Real-Time VLSI System for High Accuracy Optical Flow Estimation Using Biological Motion Features and Random Forests与哈佛大学Gang Luo教授合作成果)被SCI期刊、信息学科领域唯一入选中国科技期刊卓越行动计划期刊Science China Information Sciences接收,并获得课题组奖励

[2022-03-10]

祝贺课题组何俊贤同学(2019级博士生)主持带队的“片上***芯片”项目入选第八届中国国际“互联网+”大学生创新创业大赛重庆大学重点培育立项,获得10000元资助

[2021-12-26]

祝贺课题组王腾霄同学(2019级硕士生)带队获得“华为杯”第四届中国研究生创“芯”大赛决赛全国二等奖,并获得大赛8000元奖励

祝贺课题组杨晶同学(2019级硕士生)、李睿同学(2019级硕士生)获得“华为杯”第四届中国研究生创“芯”大赛决赛全国三等奖

[2021-10-28]

祝贺课题组全体博士生、2019级和2020级硕士生全员获得A学业奖学金(博士生1万元,硕士生8千元)

[2021-10-21]

热烈祝贺课题组杨晶同学(2019级硕士生)获得2万元研究生国家奖学金(学院排名2/165)

[2021-10-18]

祝贺课题组田敏老师成功申请获得2021年度CCF-海康威视斑头雁基金资助项目基于SRAM的高能效存内计算研究”(27万)

[2021-10-01]

祝贺课题组何祯同学(2018级本科实习生)关于类脑神经网络芯片设计的研究论文A Low-cost FPGA Implementation of Spiking Extreme Learning Machine With On-chip Reward-Modulated STDP Learning”被电路与系统领域国际知名期刊IEEE Transactions on Circuits and Systems II: Express Briefs接收,并获得课题组丰厚奖励

[2021-09-27]

祝贺课题组田敏老师成功立项重庆市博士后科学基金项目“基于忆阻器的脉冲神经网络片上学习电路设计研究”

[2021-09-25]

祝贺课题组何祯、朱玺霖同学(2018级本科实习生)成功获得研究生推免资格,其中何祯同学取得清华大学集成电路学院直博资格(加上课题组所指导的2018级大创学生,课题组本科生共4人获得保研推免资格,占本年度学校集成电路专业保研名额的50%

[2021-07-02]

祝贺课题组梁瑞奇同学(2019级本科实习生)主持带队的国家级大学生创新训练项目“轻量化三重类脑神经网络研究”成功立项

[2021-06-07]

祝贺课题组朱玺霖同学(2018级本科实习生)主持带队的大学生科研训练计划(SRTP)项目“基于压缩感知的高速实时目标跟踪芯片设计”结题获得优秀,并获得课题组奖励

[2021-03-02]

祝贺课题组王腾霄同学(2019级硕士生)脉冲神经网络深度学习的算法研究论文DeepTempo: a Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks”被电路与系统领域国际知名期刊IEEE Transactions on Circuits and Systems II: Express Briefs接收,并获得课题组丰厚奖励

[2021-01-30]

祝贺课题组王腾霄同学(2019级硕士生)脉冲神经网络深度学习的算法研究论文DeepTempo: a Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks”被国际电路与系统大会IEEE International Symposium on Circuits & Systems (ISCAS 2021)接收,并被邀请投稿至电路与系统领域国际知名期刊IEEE Transactions on Circuits and Systems II: Express Briefs,获得课题组奖励

[2020-11-17]

祝贺课题组何俊贤(2019级博士生)、喻剑依(2020级博士生)、黄进国(2018级硕士生)张杰(2018级硕士生)李睿(2019级硕士生)杨晶(2019级硕士生)王海冰(2020级硕士生)多位同学获得A等学业奖学金(博士生1万元,硕士生8千元)

[2020-11-13]

课题组推荐李睿同学(2019级硕士生)赴中国科学院计算技术研究所进行为期一年访学交流,并担任中科院计算所计算机体系结构国家重点实验室客座研究助理

[2020-11-10]

祝贺课题组王腾霄同学(2019级硕士生)关于脉冲神经网络算法的学术论文CompSNN: A Lightweight Spiking Neural Network Based on Spatiotemporally Compressive Spike Features”被SCI期刊录用,并获得课题组奖励

[2020-11-07]

热烈祝贺课题组黄进国同学(2018级硕士生)凭借在读期间优异的论文成果,破格获得普通公办高校教研岗offer

[2020-10-23]

热烈祝贺课题组张杰同学(2018级硕士生)获得2万元研究生国家奖学金(按论文成果+项目主持+竞赛获奖综合排名,全学院年级第2)

[2020-09-01]  

祝贺课题组张杰同学(2018级硕士生)关于图像目标跟踪芯片设计的学术论文“A Low-cost High-speed Object Tracking VLSI System Based on Unified Textural and Dynamic Compressive Features”被电路与系统领域国际知名期刊 IEEE Transactions on Circuits and Systems II: Express Briefs 录用并获得课题组丰厚奖励

[2020-08-16]  

祝贺课题组张杰(2018级硕士生)、李睿(2019级硕士生)、杨晶(2019级硕士生)三位同学凭借高水平科研成果,获得“兆易创新杯”第十五届研究生电子设计竞赛全国总决赛华为专项赛二等奖

[2020-06-20]  

祝贺课题组何俊贤同学(原2019级硕士生)凭借前期优异的学术成果,顺利通过硕转博申请考核,提前开始攻读博士学位


6. 发表论文

说明:*为通讯作者,分区依据为2021年底发布的最新中科院升级版

[2022]

1. Low-Cost Real-Time VLSI System for High-Accuracy Optical Flow Estimation Using Biological Motion Features and Random Forests

    Cong Shi, Junxian He, Shrinivas Pundlik, Xichuan Zhou*, Nanjian Wu, Gang Luo. Science China Information Sciences: 2022. (Accpeted) (SCI,2区)

2.  A Lightweight Spiking GAN Model for Memristor-Centric Silicon Circuit with On-Chip Reinforcement Adversarial Learning

    Jing Lu, Min Tian*, Haoran Gao, Haibing Wang, Jianyi Yu, Cong Shi. IEEE International Symposium on Circuits & Systems (ISCAS): 2022. (Accpeted)

3.  A Low-cost FPGA Implementation of Spiking Extreme Learning Machine With On-chip Reward-Modulated STDP Learning

    Zhen He, Cong Shi*, Tengxiao Wang, Ying Wang, Min Tian, Xichuan Zhou, Ping Li, Liyuan Liu, Nanjian Wu, Gang Luo. IEEE Transactions on Circuits and Systems II: Express Briefs: 2022, 69(3), pp. 1657-1661.(SCI,2区)

[2021年]

4. TripleBrain: An Edge Neuromorphic Architecture for High-accuracy Single-layer Spiking Neural Network with On-chip Self-organizing and Reinforcement Learning

     Haibing Wang, Zhen He, Jinsong Rao, Tengxiao Wang, Junxian He, Min Tian, Xichuan Zhou, Liyuan Liu, Nanjian Wu, Cong Shi*. IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA): 2021, 88-89.

5. A Pixel-Parallel Array Processor without Computational Logic for Computational Image Sensors

    Yingcheng Lin, Rui Li, Wei He, Xichuan Zhou, Junxian He, Ping Li, Liyuan Liu, Nanjian Wu, Cong Shi*. IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA): 2021, 51-52.

6. A Cost-Efficient High Speed VLSI Architecture for Spiking Convolutional Neural Network Inference Using Time-Step Binary Spike Maps

     Ling Zhang, Jing Yang, Cong Shi*, Yingcheng Lin, Wei He, Xichuan Zhou, Xu Yang, Liyuan Liu, Nanjian Wu. Sensors: 2021, 21(18), 6006. (SCI,3区)

7. DeepTempo: a Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks

     Cong Shi*, Tengxiao Wang, Junxian He, Jianghao Zhang, Liyuan Liu, Nanjian Wu. IEEE Transactions on Circuits and Systems II: Express Briefs: 2021, 68(5), 1581-1585. (SCI,2区,invited paper)

8.  An Edge 3D CNN Accelerator for Low Power Activity Recognition

     Ying Wang, Yongchen Wang, Long Cheng, Cong Shi, Huawei Li*, Xiaowei Li. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems: 2021, 40(5), 918-930. (SCI,2区)

9. Hapke Data Augmentation for Deep Learning Based Hyperspectral Data Analysis with Limited Samples

     Kai Qin, Fangyuan Ge, Yingjun Zhao, Ling Zhu, Ming Li, Cong Shi, Dong Li, Xichuang Zhou*. IEEE Geoscience and Remote Sensing Letters: 2021, 18(5), 886-890.SCI,2区)

10. Exploiting Memristors for Neuromorphic Reinforcement Learning

     Cong Shi, Jing Lu, Ying Wang, Ping Li, Min Tian*. IEEE International Conference on Artificial Intelligence Circuits & Systems (AICAS): 2021: 2021, 1-5.

11.  A Low-cost High-speed Object Tracking VLSI System Based on Unified Textural and Dynamic Compressive Features

    Wei He, Jie Zhang, Yingcheng Lin, Xichuan Zhou, Ping Li, Liyuan Liu, Nanjian Wu, Cong Shi*. IEEE Transactions on Circuits and Systems II: Express Briefs: 2021, 68(3), 1013-1017.(SCI,2区)

12.  A Novel Approach to Inactivate the Body p-i-n Diode of SiC MOSFET by Using the Normally-off JFET

    Ping Li, Jingwei Guo, Zhi Lin, Shengdong Hu, Cong Shi, Fang Tang*. IEEE Transactions on Electron Devices: 2021, 68(4), 1784-1790.(SCI,2区)

13. A Heterogeneous Spiking Neural Network for Computationally Efficient Face Recognition

     Xichuan Zhou, Zhenghua Zhou, Zhengqing Zhong, Jianyi Yu, Tengxiao Wang, Min Tian, Ying Jiang, Cong Shi*. IEEE International Symposium on Circuits & Systems (ISCAS): 2021, 1-5.

14. Optimizing Information Theory Based Bitwise Bottlenecks for Efficient Mixed-Precision Activation Quantization

    Xichuan Zhou*, Kui Liu, Cong Shi, Haijun Liu, Ji Liu. AAAI Conference on Artificial Intelligence (AAAI): 35(4), 3590-3598, 2021.

15. CompSNN: A Lightweight Spiking Neural Network Based on Spatiotemporally Compressive Spike Features

     Tengxiao Wang, Cong Shi*, Xichuan Zhou, Yingcheng Lin, Junxian He, Ping Gan, Ping Li, Ying Wang, Liyuan Liu, Nanjian Wu, Gang Luo. Neurocomputing: 2021, 425(15), 96-106. SCI,2区)

[2020]

16. BitPruner: Network Pruning for Bit-serial Accelerators

     Xiandong Zhao, Ying Wang*, Cheng Liu, Cong Shi, Kaijie Tu, Lei Zhang. ACM/IEEE Design Automation Conference (DAC): 2020, No. 47, 1-6.

17. A High-speed Low-cost CNN Inference Accelerator for Depthwise Separable Convolution

     Yingcheng Lin, Rui Li, Wei He, Xichuan Zhou, Junxian He, Ping Li, Ying Jiang, Liyuan Liu, Nanjian Wu, Cong Shi*. IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA): 2020, 63-64.

18.  A High-speed Low-cost VLSI System Capable of On-chip Online Learning for Dynamic Vision Sensor Data Classification

     Wei He, Jinguo Huang, Tengxiao Wang, Yingcheng Lin, Junxian He, Xichuan Zhou, Ping Li, Ying Wang, Nanjian Wu, Cong Shi*. Sensors: 2020, 20(17), 4715. (SCI,3区)

19.  Without low spatial frequencies, high resolution vision would be detrimental to motion perception

     Cong Shi*, Shrinivas Pundlik, Gang Luo*. Journal of Vision: 2020, 20(8), 29.  (SCI,3区)

20.  MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time

     Xichuan Zhou*, Yicong Peng, Chunqiao Long, Fengbo Ren, Cong Shi. International Conference on Machine Learning (ICML): no. 119,11503-11512, 2020.

21.  A Low Reverse Recovery Charge Superjunction MOSFET with P-base and N-pillar Schottky Contacts

     Ping Li*, Zhi Lin, Shengdong Hu, Cong Shi, Fang Tang. IEEE Transactions on Electron Devices: 2020, 67(4), 1693-1698. SCI,2区)

[2019]

22.   A Hardware System for Fast AER Object Classification with On-chip Online Learning

     Jinguo Huang, Wei He, Xichuan Zhou, Junxian He, Ying Wang, Cong Shi, Yingcheng Lin*. IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA): 2019, 85-86.

23.    High-speed Classification of AER Data Based on a Low-cost Hardware System

      Jinguo Huang, Yingcheng Lin, Wei He, Xichuan Zhou, Cong Shi*, Nanjian Wu, Gang Luo. IEEE International Conference on ASIC (ASICON): 2019, 1-4.

24.   20,000-fps Visual Motion Magnification on Pixel-parallel Vision Chip

     Junxian He, Xichuan Zhou, Yingcheng Lin, Chonglei Sun, Cong Shi*, Nanjian Wu, Gang Luo. IEEE International Conference on ASIC (ASICON): 2019, 1-4.

25.    基于仿生运动能量特征的光流计算芯片设计综述

     何俊贤, 黄进国, 石匆*. 微纳电子与智能制造: 2019, 1(3), 141-150.

26.   Systolic Cube: A Spatial 3D CNN Accelerator Architecture for Low Power Video Analysis

     Yongchen Wang, Ying Wang, Huawei Li, Cong Shi, Xiaowei Li*. IEEE/ACM Design Automation Confernece (DAC): 2019, No. 210, 1-6.

27.   A Hardware-Friendly Optical Flow-Based Time-to-Collision Estimation Algorithm

     Cong Shi*, Zhuoran Dong, Shrinivas Pundlik, Gang Luo. Sensors: 2019, 19(4), 807. (SCI,3区)

[2018]

28.   A Streaming Motion Magnification Core for Smart Image Sensors

      Cong Shi*, Gang Luo. IEEE Transactions on Circuits and Systems II: Express Briefs: 2018, 65(9), 1229-1233. (SCI,2区)

29.  Comparison of computerized system and human observers for vision assessment based on optomotor response in Rhodopsin knockout mice

      Kin-Sang Cho, Jiaxin Xiao, Cong Shi, Karen Chang, Tor Paaske Utheim, Gang Luo, Dong Feng Chen*. Investigative Ophthalmology & Visual Science: 2018, 59(9), 982. (SCI,2区)

30.  A Compact VLSI System for Bio-Inspired Visual Motion Estimation

      Cong Shi, Gang Luo*. IEEE Transactions on Circuits and Systems for Video Technology: 2018, 28(4), 1021-1036. (SCI,1区)

31.  Exploiting Lightweight Statistical Learning for Event-Based Vision Processing

     Cong Shi, Jiajun Li, Ying Wang*, Gang Luo. IEEE Access: 2018,6, 19396-19406. (SCI,3区)

32.  Optimization of Optomotor Response-based Visual Function Assessment in Mice

Cong Shi*, Xuedong Yuan, Karen Chang, Kin-Sang Cho, Xinmin Simon Xie, Dong Feng Chen, Gang Luo. Scientific Reports: 2018, 8(1), 9708. (SCI,3区)

[2017年以前]

33.  662: Comparison of Flat and Curved Monitors: Eyestrain Caused by Intensive Visual Search Task

      Gang Luo*, Ying Chen, Amy Doherty, Rui Liu, Cong Shi, Shuhang Wang, Hoai Le, Eli Peli. SID Symposium Digest of Technical Papers: 2016, 47(1), 903-906

34.  High speed vision processor with reconfigurable processing element array based on full-custom distributed memory

      Zhe Chen, Jie Yang, Cong Shi, Qi Qin, Liyuan Liu, Nanjian Wu*. Japanese Journal of Applied Physics: 2016, 55(4S), 04EF08. (SCI,4区)

35.  A low power global shutter pixel with extended FD voltage swing range for large format high speed CMOS image sensor

      Yangfan Zhou, Zhongxiang Cao, Ye Han, Quanliang Li, Cong Shi, Runjian Dou, Qi Qin, Jian Liu, Nanjian Wu*. Science China Information Sciences: 2015, 58(4), 1-10. (SCI,2区)

36.  Pixel-parallel feature detection on vision chip

      Jie Yang, Cong Shi, Liyuan Liu, Jian Liu, Nanjian Wu*. Electronics Letters: 2014, 50(24), 1839-1841. (SCI,4区)

37. A massively parallel keypoint detection and description (MP-KDD) algorithm for high-speed vision chip

       Cong Shi, Jie Yang, Liyuan Liu, Nanjian Wu*, Zhihua Wang. Science China Information Sciences: 2014, 57(10), 1-12. (SCI,2区)

38.  A reconfigurable 256 × 256 image sensor controller that is compatible for depth measurement

      Zhe Chen, Shan Di, Cong Shi, Liyuan Liu, Nanjian Wu*. Chinese Journal of Semiconductors: 2014,35(10), 105007-6.

39.  A 1000 fps vision chip based on a dynamically reconfigurable hybrid architecture comprising a PE array processor and self-organizing map neural network

      Cong Shi, Jie Yang, Ye Han, Zhongxiang Cao, Qi Qin, Liyuan Liu, Nan-Jian Wu*, Zhihua Wang. IEEE Journal of Solid-State Circuits: 2014, 49(9), 2067-2082. (SCI,1区,集成电路设计最顶级期刊)

40. A compact PE memory for vision chip

      Cong Shi, Zhe Chen, Jie Yang, Nanjian Wu*, Zhihua Wang. Chinese Journal of Semiconductors: 2014, 35(9), 095002-7.

41. A high speed multi-level-parallel array processor for vision chips

      Cong Shi, Jie Yang, Nanjian Wu*, Zhihua Wang. Science China Information Sciences: 2014, 57(6), 1-12. (SCI,2区)

42.  A high speed 1000 fps CMOS image sensor with low noise global shutter pixels

      Yangfan Zhou, Zhongxiang Cao, Qi Qin, Quanliang Li, Cong Shi, Nanjian Wu*. Science China Information Sciences: 2014, 57(4), 1-8. (SCI,2区)

43.  Heterogeneous vision chip and a LBP based algorithm for high-speed tracking

      Jie Yang, Cong Shi, Liyuan Liu, Nanjian Wu*. Electronics Letters: 2014, 50(6),438-439. (SCI,4区)

44.  7.3 A1000fps vision chip based on a dynamically reconfigurable hybrid architecture comprising a PE array and self-organizing map neural network

      Cong Shi, Jie Yang, Ye Han, Zhongxiang Cao, Qi Qin, Liyuan Liu, Nan-Jian Wu*, Zhihua Wang. IEEE International Solid-State Circuits Conference (ISSCC): 2014, 128-129. (集成电路设计最顶级会议)

45.  Smart image sensing system

      Jie Yang, Cong Shi, Zhongxiang Cao, Ye Han, Liyuan Liu, Nanjian Wu*. IEEE Sensors Conference:2013, 1-4.

46.  A novel architecture of local memory for programmable SIMD vision chip

      Zhe Chen, Jie Yang, Cong Shi, Nanjian Wu*. IEEE International Conference on ASIC (ASICON): 2013, 1-4.

47.  A programmable computational image sensor for high-speed vision

      Jie Yang, Cong Shi, Xitian Long, Nanjian Wu*. International Symposium on Photoelectronic Detectionand Imaging (ISPDI): 2013, 89081T-6.

48. A 10-bit column-parallel cyclic ADC for high-speed CMOS image sensors

      Ye Han, Quanliang Li, Cong Shi, Nanjian Wu*. Chinese Journal of Semiconductors: 2013, 34(8), 085016-6.

49.  A Programmable High Speed Vision System with Superscalar PE and Its Parallel Computing Language

      Jie Yang, Cong Shi, Xitian Long, Nanjian Wu*. Open Journal of Applied Sciences: 2013, 3(1B), 65-67.

50.  A low-power column-parallel ADC for high-speed CMOS image sensor

      Ye Han, Quanliang Li, Cong Shi, Liyuan Liu, Nanjian Wu*. International Symposium on Photoelectronic Detection and Imaging (ISPDI): 2013, 89082E-7.

51.  一种基于多级并行处理器的高速实时手势识别及指尖轨迹追踪系统

      龙希田, 石匆, 杨杰, 吴南健*. 微电子学与计算机: 2013, 30(12), 90-96.

52.  A high-speed CMOS image sensor with column-parallel single capacitor CDSs and single-slope ADCs

      Quanliang Li, Cong Shi, Nanjian Wu*. International Symposium on Photoelectronic Detection and Imaging (ISPDI): 2011,819433-6.

53.  A high-speed vision processor based on pixel-parallel PE array and its applications

      Cong Shi, Nanjian Wu*, Zhihua Wang. IEEE Youth Conference on Information Computing and Telecommunications (YC-ICT): 2010, 57-60.

54.  DSTN sleep transistor sizing with a new approach to estimate the maximum instantaneous current

      Yu Sun, Liyi Xiao*, Cong Shi. IEEE International Symposium on Circuits and Systems (ISCAS): 2010, 3717-3720.

55.  功率门控技术中的分簇算法和控制电路

      张利地, 肖立伊*, 石匆. 微处理机: 2009, 30(5), 31-34.


7. 发明专利

1. 基于脉冲神经网络的轻量级片上学习方法、系统及处理器. 王海冰, 石匆*, 田敏, 王腾霄, 何俊贤, 何祯. 中国,公开号:CN114091663A,2022-2-25

2. 基于脉冲神经网络的实时深度学习方法、系统及处理器.王腾霄, 石匆*, 田敏, 何俊贤, 王海冰, 喻剑依. 中国,公开号:CN114065922A,2022-2-18

3. 基于时间步的二值脉冲图的脉冲卷积神经网络硬件加速器. 张玲, 杨晶, 石匆*, 林英撑, 何伟, 李睿. 中国,公开号:CN113033795A2021-6-25

4. 基于深度可分离卷积的轻量级神经网络硬件加速器. 林英撑, 李睿, 石匆*, 何伟, 张玲, 杨晶. 中国,公开号:CN113033794A2021-6-25

5. Assessing Visual Function. Dong Feng Chen, Gang Luo*, Cong Shi, Kin-Sang Cho. 美国,US 17/044,606,2020-10-1

6. Dynamically reconstructable multistage parallel single instruction multiple data array processing system. Cong Shi, Nanjian Wu*, Xitian Long, Jie Yang, Qi Qin. 美国,US9449257 B2,2016-9-20

7. 可动态重构的多级并行单指令多数据阵列处理系统. 石匆,吴南健*,龙希田,杨杰,秦琦. 中国,ZL201210512880.1,2016-4-27

8. 多端口读写的片内存储器. 龙希田,杨杰,石匆,吴南健*. 中国,ZL201310140319.X2016-1-20

9. 基于多层次并行处理的视觉处理装置. 杨杰,吴南健*,石匆,龙希田. 中国,ZL201210548515.62015-11-14

10. 基于可编程视觉芯片的视觉图像处理系统. 石匆,吴南健*,龙希田,杨杰,秦琦. 中国,ZL201210088420.02014-9-17

11. 一种多步单斜模拟数字信号转换装置. 李全良,吴南健*,韩烨,石匆. 中国,ZL201210015324.32014-5-14

12. 分布式休眠管功率门控电路中最大翻转电流的静态估算方法. 肖立伊*,孙宇,石匆. 中国,ZL200910072733.52011-7-27