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2020 – today
- 2024
[j4]Fangxin Liu
, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Xiaoyao Liang, Li Jiang:
ERA-BS: Boosting the Efficiency of ReRAM-Based PIM Accelerator With Fine-Grained Bit-Level Sparsity. IEEE Trans. Computers 73(9): 2320-2334 (2024)- 2023
- [j3]Fangxin Liu, Zongwu Wang, Yongbiao Chen, Zhezhi He, Tao Yang, Xiaoyao Liang, Li Jiang:
SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(1): 204-217 (2023) - [j2]Yongbiao Chen, Sheng Zhang, Fangxin Liu, Chenggang Wu, Kaicheng Guo, Zhengwei Qi:
DVHN: A Deep Hashing Framework for Large-Scale Vehicle Re-Identification. IEEE Trans. Intell. Transp. Syst. 24(9): 9268-9280 (2023) - [c13]Fangxin Liu, Haoming Li, Yongbiao Chen, Tao Yang, Li Jiang:
HyperAttack: An Efficient Attack Framework for HyperDimensional Computing. DAC 2023: 1-6 - 2022
- [j1]Chenggang Wu, Yongbiao Chen, Zhengwei Qi, Haibing Guan:
DSPR: Secure decentralized storage with proof-of-replication for edge devices. J. Syst. Archit. 125: 102441 (2022) - [c12]Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Li Jiang:
SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks. AAAI 2022: 1692-1701 - [c11]Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang:
EBSP: evolving bit sparsity patterns for hardware-friendly inference of quantized deep neural networks. DAC 2022: 259-264 - [c10]Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Zhezhi He, Rui Yang, Qidong Tang, Tao Yang, Cheng Zhuo, Li Jiang:
PIM-DH: ReRAM-based processing-in-memory architecture for deep hashing acceleration. DAC 2022: 1087-1092 - [c9]Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Tao Yang, Zhezhi He, Xiaokang Yang, Li Jiang:
SATO: spiking neural network acceleration via temporal-oriented dataflow and architecture. DAC 2022: 1105-1110 - [c8]Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Fei Dai:
DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks. ICASSP 2022: 2130-2134 - [c7]Fangxin Liu, Zongwu Wang, Wenbo Zhao, Yongbiao Chen, Tao Yang, Xiaokang Yang, Li Jiang:
Randomize and Match: Exploiting Irregular Sparsity for Energy Efficient Processing in SNNs. ICCD 2022: 451-454 - [c6]Yongbiao Chen, Kaicheng Guo, Fangxin Liu, Yusheng Huang, Zhengwei Qi:
Supervised Contrastive Vehicle Quantization for Efficient Vehicle Retrieval. ICMR 2022: 44-48 - [c5]Yongbiao Chen, Sheng Zhang, Fangxin Liu, Zhigang Chang, Mang Ye, Zhengwei Qi:
TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval. ICMR 2022: 127-136 - 2021
- [c4]Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Yongbiao Chen, Li Jiang:
Bit-Transformer: Transforming Bit-level Sparsity into Higher Preformance in ReRAM-based Accelerator. ICCAD 2021: 1-9 - [c3]Yang Wen, Leiting Chen, Haisheng Chen, Ximan Tang, Yu Deng, Yongbiao Chen, Chuan Zhou:
Non-Local Attention Learning for Medical Image Classification. ICME 2021: 1-6 - [c2]Zhigang Chang, Zhao Yang, Yongbiao Chen, Qin Zhou, Shibao Zheng:
Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification. VCIP 2021: 1-5 - [i3]Yongbiao Chen, Sheng Zhang, Fangxin Liu, Zhigang Chang, Mang Ye, Zhengwei Qi:
TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval. CoRR abs/2105.01823 (2021) - [i2]Yongbiao Chen, Sheng Zhang, Fangxin Liu, Chenggang Wu, Kaicheng Guo, Zhengwei Qi:
DVHN: A Deep Hashing Framework for Large-scale Vehicle Re-identification. CoRR abs/2112.04937 (2021) - [i1]Zhigang Chang, Zhao Yang, Yongbiao Chen, Qin Zhou, Shibao Zheng:
Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification. CoRR abs/2112.05626 (2021) - 2020
- [c1]Yongbiao Chen, Sheng Zhang, Zhengwei Qi:
MAENet: Boosting Feature Representation for Cross-Modal Person Re-Identification with Pairwise Supervision. ICMR 2020: 442-449
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