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ORCIDCong Shi 0003
Person information
- affiliation: Chongqing University, School of Microelectronics and Communication Engineerin, China
- affiliation: Harvard Medical School, Schepens Eye Research Institute, Massachusetts Eye and Ear, Boston, MA, USA
- affiliation (PhD 2014): Tsinghua University, Beijing, China
- affiliation (PhD 2014): Chinese Academy of Sciences, Institute of Semiconductors, Beijing, China
Other persons with the same name
- Cong Shi — disambiguation page
- Cong Shi 0001
![[0000-0003-3564-3391]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-3564-3391")
— University of Michigan, Ann Arbor, MI, USA - Cong Shi 0002 — Beijing University of Posts and Telecommunications, MOE, Key Laboratory of Universal Wireless Communications, China
- Cong Shi 0004 — Rutgers University, New Brunswick, NJ, USA (and 1 more)
- Cong Shi 0005 — Georg-August-Universität Göttingen, Germany
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2020 – today
- 2024
[j27]Li Wang, Cong Shi, Shrinivas J. Pundlik, Xu Yang, Liyuan Liu, Gang Luo:
LLD-GAN: An end-to-end network for low-light image demosaicking. Displays 85: 102856 (2024)- [j26]Siyuan Wei, Ke Ning, Lei Kang, Xuemin Zheng, Mingxin Zhao, Mengmeng Xu, Shuyu Wang, Xuanzhe Xu, Runjiang Dou, Shuangming Yu, Xu Yang, Jian Liu, Cong Shi, Nanjian Wu, Liyuan Liu:
A Real-Time 2D/3D Perception Visual Vector Processor for 1920 × 1080 High-Resolution High-Speed Intelligent Vision Chips. IEEE Trans. Circuits Syst. I Regul. Pap. 71(2): 740-753 (2024) - [j25]Cong Shi, Xiang Fu, Haibing Wang, Yingcheng Lin, Ying Jiang, Liyuan Liu, Nanjian Wu, Min Tian:
Ghost Reservoir: A Memory-Efficient Low-Power and Real-Time Neuromorphic Processor of Liquid State Machine With On-Chip Learning. IEEE Trans. Circuits Syst. II Express Briefs 71(10): 4526-4530 (2024) - 2023
- [j24]Cong Shi, Junxian He, Shrinivas J. Pundlik, Xichuan Zhou, Nanjian Wu, Gang Luo:
Low-cost real-time VLSI system for high-accuracy optical flow estimation using biological motion features and random forests. Sci. China Inf. Sci. 66(5) (2023) - [j23]Cong Shi, Li Wang, Haoran Gao, Min Tian:
Learnable Leakage and Onset-Spiking Self-Attention in SNNs with Local Error Signals. Sensors 23(24): 9781 (2023) - [j22]Xiandong Zhao, Ying Wang, Cheng Liu, Cong Shi, Kaijie Tu, Lei Zhang:
Network Pruning for Bit-Serial Accelerators. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(5): 1597-1609 (2023) - [j21]Leyi Chen, Cong Shi, Junxian He, Jianyi Yu, Haibing Wang, Jing Lu, Liyuan Liu, Nanjian Wu, Min Tian:
An 8-T Processing-in-Memory SRAM Cell-Based Pixel-Parallel Array Processor for Vision Chips. IEEE Trans. Circuits Syst. I Regul. Pap. 70(11): 4249-4259 (2023) - [j20]Cong Shi, Jingya Zhang, Tengxiao Wang, Zhengqing Zhong, Junxian He, Haoran Gao, Jianyi Yu, Ping Li, Min Tian:
An Edge Neuromorphic Hardware With Fast On-Chip Error-Triggered Learning on Compressive Sensed Spikes. IEEE Trans. Circuits Syst. II Express Briefs 70(7): 2665-2669 (2023) - [j19]Lei Kang, Xu Yang, Chi Zhang, Shuangming Yu, Runjiang Dou, Wenchang Li, Cong Shi, Jian Liu, Nanjian Wu, Liyuan Liu:
A 24.3 μJ/Image SNN Accelerator for DVS-Gesture With WS-LOS Dataflow and Sparse Methods. IEEE Trans. Circuits Syst. II Express Briefs 70(11): 4226-4230 (2023) - [c19]Zhengqing Zhong, Tengxiao Wang, Haibing Wang, Zhihua Zhou, Junxian He, Fang Tang, Xichuan Zhou, Shuangming Yu, Liyuan Liu, Nanjian Wu, Min Tian, Cong Shi:
Live Demonstration: Face Recognition at The Edge Using Fast On-Chip Deep Learning Neuromorphic Chip. AICAS 2023: 1-2 - [c18]Tengxiao Wang, Min Tian, Zhengqing Zhong, Haibing Wang, Junxian He, Fang Tang, Xichuan Zhou, Shuangming Yu, Nanjian Wu, Liyuan Liu, Cong Shi:
MorphBungee: A 65nm 7.2mm2 27μJ/image Digital Edge Neuromorphic Chip with On-Chip 802 Frame/s Multi-Layer Spiking Neural Network Learning. A-SSCC 2023: 1-3 - [c17]Fuming Lei, Xu Yang, Jian Liu, Nanjian Wu, Cong Shi, Runjiang Dou, Liyuan Liu:
A Lightweight Integer-STBP On-Chip Learning Method of Spiking Neural Networks For Edge Processors. ICTA 2023: 1-2 - 2022
- [j18]Haibing Wang, Zhen He, Tengxiao Wang, Junxian He, Xichuan Zhou, Ying Wang, Liyuan Liu, Nanjian Wu, Min Tian, Cong Shi:
TripleBrain: A Compact Neuromorphic Hardware Core With Fast On-Chip Self-Organizing and Reinforcement Spike-Timing Dependent Plasticity. IEEE Trans. Biomed. Circuits Syst. 16(4): 636-650 (2022) - [j17]Zhen He, Cong Shi, Tengxiao Wang, Ying Wang, Min Tian, Xichuan Zhou, Ping Li, Liyuan Liu, Nanjian Wu, Gang Luo:
A Low-Cost FPGA Implementation of Spiking Extreme Learning Machine With On-Chip Reward-Modulated STDP Learning. IEEE Trans. Circuits Syst. II Express Briefs 69(3): 1657-1661 (2022) - [c16]Leyi Chen, Junxian He, Jianyi Yu, Haibing Wang, Jing Lu, Liyuan Liu, Nanjian Wu, Cong Shi, Min Tian:
An 8-T Processing-in-Memory SRAM Cell-Based Pixel-Parallel Array Processor for Vision Chips. APCCAS 2022: 1-5 - [c15]Tengxiao Wang, Haibing Wang, Junxian He, Zhengqing Zhong, Fang Tang, Xichuan Zhou, Shuangming Yu, Liyuan Liu, Nanjian Wu, Min Tian, Cong Shi:
MorphBungee: An Edge Neuromorphic Chip for High-Accuracy On-Chip Learning of Multiple-Layer Spiking Neural Networks. BioCAS 2022: 255-259 - [c14]Min Tian, Jing Lu, Haoran Gao, Haibing Wang, Jianyi Yu, Cong Shi:
A Lightweight Spiking GAN Model for Memristor-centric Silicon Circuit with On-chip Reinforcement Adversarial Learning. ISCAS 2022: 3388-3392 - 2021
- [j16]Tengxiao Wang, Cong Shi, Xichuan Zhou, Yingcheng Lin, Junxian He, Ping Gan, Ping Li, Ying Wang, Liyuan Liu, Nanjian Wu, Gang Luo:
CompSNN: A lightweight spiking neural network based on spatiotemporally compressive spike features. Neurocomputing 425: 96-106 (2021) - [j15]Kai Qin, Fangyuan Ge, Yingjun Zhao, Ling Zhu, Ming Li, Cong Shi, Dong Li, Xichuan Zhou:
Hapke Data Augmentation for Deep Learning-Based Hyperspectral Data Analysis With Limited Samples. IEEE Geosci. Remote. Sens. Lett. 18(5): 886-890 (2021) - [j14]Ling Zhang, Jing Yang, Cong Shi, Yingcheng Lin, Wei He, Xichuan Zhou, Xu Yang, Liyuan Liu, Nanjian Wu:
A Cost-Efficient High-Speed VLSI Architecture for Spiking Convolutional Neural Network Inference Using Time-Step Binary Spike Maps. Sensors 21(18): 6006 (2021) - [j13]Ying Wang, Yongchen Wang, Cong Shi, Long Cheng, Huawei Li, Xiaowei Li:
An Edge 3D CNN Accelerator for Low-Power Activity Recognition. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 40(5): 918-930 (2021) - [j12]Wei He, Jie Zhang, Yingcheng Lin, Xichuan Zhou, Ping Li, Liyuan Liu, Nanjian Wu, Cong Shi:
A Low-Cost High-Speed Object Tracking VLSI System Based on Unified Textural and Dynamic Compressive Features. IEEE Trans. Circuits Syst. II Express Briefs 68(3): 1013-1017 (2021) - [j11]Cong Shi, Tengxiao Wang, Junxian He, Jianghao Zhang, Liyuan Liu, Nanjian Wu:
DeepTempo: A Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks. IEEE Trans. Circuits Syst. II Express Briefs 68(5): 1581-1585 (2021) - [c13]Xichuan Zhou, Kui Liu, Cong Shi, Haijun Liu, Ji Liu:
Optimizing Information Theory Based Bitwise Bottlenecks for Efficient Mixed-Precision Activation Quantization. AAAI 2021: 3590-3598 - [c12]Cong Shi, Jing Lu, Ying Wang, Ping Li, Min Tian:
Exploiting Memristors for Neuromorphic Reinforcement Learning. AICAS 2021: 1-4 - [c11]Yingcheng Lin, Rui Li, Wei He, Xichuan Zhou, Junxian He, Ping Li, Liyuan Liu, Nanjian Wu, Cong Shi:
A Pixel-Parallel Array Processor without Computational Logic for Computational Image Sensors. ICTA 2021: 51-52 - [c10]Haibing Wang, Zhen He, Jinsong Rao, Tengxiao Wang, Junxian He, Min Tian, Xichuan Zhou, Liyuan Liu, Nanjian Wu, Cong Shi:
TripleBrain: An Edge Neuromorphic Architecture for High-accuracy Single-layer Spiking Neural Network with On-chip Self-organizing and Reinforcement Learning. ICTA 2021: 88-89 - [c9]Xichuan Zhou, Zhenghua Zhou, Zhengqing Zhong, Jianyi Yu, Tengxiao Wang, Min Tian, Ying Jiang, Cong Shi:
A Heterogeneous Spiking Neural Network for Computationally Efficient Face Recognition. ISCAS 2021: 1-5 - 2020
- [j10]Wei He, Jinguo Huang, Tengxiao Wang, Yingcheng Lin, Junxian He, Xichuan Zhou, Ping Li, Ying Wang, Nanjian Wu, Cong Shi:
A High-Speed Low-Cost VLSI System Capable of On-Chip Online Learning for Dynamic Vision Sensor Data Classification. Sensors 20(17): 4715 (2020) - [c8]Xiandong Zhao, Ying Wang, Cheng Liu, Cong Shi, Kaijie Tu, Lei Zhang:
BitPruner: Network Pruning for Bit-serial Accelerators. DAC 2020: 1-6 - [c7]Xichuan Zhou, Yicong Peng, Chunqiao Long, Fengbo Ren, Cong Shi:
MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time. ICML 2020: 11503-11512 - [c6]Yingcheng Lin, Rui Li, Wei He, Xichuan Zhou, Junxian He, Ping Li, Ying Jiang, Liyuan Liu, Nanjian Wu, Cong Shi:
A High-speed Low-cost CNN Inference Accelerator for Depthwise Separable Convolution. ICTA 2020: 63-64 - [i2]Xichuan Zhou, Kui Liu, Cong Shi, Haijun Liu, Ji Liu:
Neural Network Activation Quantization with Bitwise Information Bottlenecks. CoRR abs/2006.05210 (2020) - [i1]Xichuan Zhou, Yicong Peng, Chunqiao Long, Fengbo Ren, Cong Shi:
MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time. CoRR abs/2006.16007 (2020)
2010 – 2019
- 2019
- [j9]Cong Shi, Zhuoran Dong, Shrinivas J. Pundlik, Gang Luo:
A Hardware-Friendly Optical Flow-Based Time-to-Collision Estimation Algorithm. Sensors 19(4): 807 (2019) - [c5]Junxian He, Xichuan Zhou, Yingcheng Lin, Chonglei Sun, Cong Shi, Nanjian Wu, Gang Luo:
20, 000-fps Visual Motion Magnification on Pixel-parallel Vision Chip. ASICON 2019: 1-4 - [c4]Jinguo Huang, Yingcheng Lin, Wei He, Xichuan Zhou, Cong Shi, Nanjian Wu, Gang Luo:
High-speed Classification of AER Data Based on a Low-cost Hardware System. ASICON 2019: 1-4 - [c3]Yongchen Wang, Ying Wang, Huawei Li, Cong Shi, Xiaowei Li:
Systolic Cube: A Spatial 3D CNN Accelerator Architecture for Low Power Video Analysis. DAC 2019: 210 - 2018
- [j8]Cong Shi, Jiajun Li, Ying Wang, Gang Luo:
Exploiting Lightweight Statistical Learning for Event-Based Vision Processing. IEEE Access 6: 19396-19406 (2018) - [j7]Cong Shi, Gang Luo:
A Streaming Motion Magnification Core for Smart Image Sensors. IEEE Trans. Circuits Syst. II Express Briefs 65-II(9): 1229-1233 (2018) - [j6]Cong Shi, Gang Luo:
A Compact VLSI System for Bio-Inspired Visual Motion Estimation. IEEE Trans. Circuits Syst. Video Technol. 28(4): 1021-1036 (2018) - 2015
- [j5]Yangfan Zhou, Zhongxiang Cao, Ye Han, Quanliang Li, Cong Shi, Runjiang Dou, Qi Qin, Jian Liu, Nanjian Wu:
A low power global shutter pixel with extended FD voltage swing range for large format high speed CMOS image sensor. Sci. China Inf. Sci. 58(4): 1-10 (2015) - 2014
- [j4]Yangfan Zhou, Zhongxiang Cao, Qi Qin, Quanliang Li, Cong Shi, Nanjian Wu:
A high speed 1000 fps CMOS image sensor with low noise global shutter pixels. Sci. China Inf. Sci. 57(4): 1-8 (2014) - [j3]Cong Shi, Jie Yang, Nanjian Wu, ZhiHua Wang:
A high speed multi-level-parallel array processor for vision chips. Sci. China Inf. Sci. 57(6): 1-12 (2014) - [j2]Cong Shi, Jie Yang, Liyuan Liu, Nanjian Wu, ZhiHua Wang:
A massively parallel keypoint detection and description (MP-KDD) algorithm for high-speed vision chip. Sci. China Inf. Sci. 57(10): 1-12 (2014) - [j1]Cong Shi, Jie Yang, Ye Han, Zhongxiang Cao, Qi Qin, Liyuan Liu, Nanjian Wu, Zhihua Wang:
A 1000 fps Vision Chip Based on a Dynamically Reconfigurable Hybrid Architecture Comprising a PE Array Processor and Self-Organizing Map Neural Network. IEEE J. Solid State Circuits 49(9): 2067-2082 (2014) - [c2]Cong Shi, Jie Yang, Ye Han, Zhongxiang Cao, Qi Qin, Liyuan Liu, Nanjian Wu, Zhihua Wang:
7.3 A 1000fps vision chip based on a dynamically reconfigurable hybrid architecture comprising a PE array and self-organizing map neural network. ISSCC 2014: 128-129 - 2013
- [c1]Zhe Chen, Jie Yang, Cong Shi, Nanjian Wu:
A novel architecture of local memory for programmable SIMD vision chip. ASICON 2013: 1-4
Coauthor Index
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