MAENet: Boosting Feature Representation for Cross-Modal Person Re-Identification with Pairwise Supervision. - Yongbiao Chen; Sheng Zhang; Zhengwei Qi (ICMR, 2020)

Bit-Transformer: Transforming Bit-level Sparsity into Higher Preformance in ReRAM-based Accelerator. - Fangxin Liu; Wenbo Zhao 005; Zhezhi He; Zongwu Wang; Yilong Zhao; Yongbiao Chen; Li Jiang 002 (ICCAD, 2021)

Non-Local Attention Learning for Medical Image Classification. - Yang Wen; Leiting Chen; Haisheng Chen; Ximan Tang; Yu Deng 005; Yongbiao Chen; Chuan Zhou 004 (ICME, 2021)

Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification. - Zhigang Chang; Zhao Yang; Yongbiao Chen; Qin Zhou; Shibao Zheng (VCIP, 2021)

SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks. - Fangxin Liu; Wenbo Zhao 005; Yongbiao Chen; Zongwu Wang; Li Jiang 002 (AAAI, 2022)

PIM-DH: ReRAM-based processing-in-memory architecture for deep hashing acceleration. - Fangxin Liu; Wenbo Zhao 005; Yongbiao Chen; Zongwu Wang; Zhezhi He; Rui Yang; Qidong Tang; Tao Yang 031; Cheng Zhuo; Li Jiang 002 (DAC, 2022)

EBSP: evolving bit sparsity patterns for hardware-friendly inference of quantized deep neural networks. - Fangxin Liu; Wenbo Zhao 005; Zongwu Wang; Yongbiao Chen; Zhezhi He; Naifeng Jing; Xiaoyao Liang; Li Jiang 002 (DAC, 2022)

SATO: spiking neural network acceleration via temporal-oriented dataflow and architecture. - Fangxin Liu; Wenbo Zhao 005; Zongwu Wang; Yongbiao Chen; Tao Yang 031; Zhezhi He; Xiaokang Yang 001; Li Jiang 002 (DAC, 2022)

DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks. - Fangxin Liu; Wenbo Zhao 005; Yongbiao Chen; Zongwu Wang; Fei Dai 008 (ICASSP, 2022)

Randomize and Match: Exploiting Irregular Sparsity for Energy Efficient Processing in SNNs. - Fangxin Liu; Zongwu Wang; Wenbo Zhao 005; Yongbiao Chen; Tao Yang 031; Xiaokang Yang 001; Li Jiang 002 (ICCD, 2022)

Supervised Contrastive Vehicle Quantization for Efficient Vehicle Retrieval. - Yongbiao Chen; Kaicheng Guo; Fangxin Liu; Yusheng Huang; Zhengwei Qi (ICMR, 2022)

TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval. - Yongbiao Chen; Sheng Zhang; Fangxin Liu; Zhigang Chang; Mang Ye; Zhengwei Qi (ICMR, 2022)

DSPR: Secure decentralized storage with proof-of-replication for edge devices. - Chenggang Wu; Yongbiao Chen; Zhengwei Qi; Haibing Guan (J. Syst. Archit., 2022)

HyperAttack: An Efficient Attack Framework for HyperDimensional Computing. - Fangxin Liu; Haomin Li 002; Yongbiao Chen; Tao Yang 031; Li Jiang 002 (DAC, 2023)

SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator. - Fangxin Liu; Zongwu Wang; Yongbiao Chen; Zhezhi He; Tao Yang 031; Xiaoyao Liang; Li Jiang 002 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

DVHN: A Deep Hashing Framework for Large-Scale Vehicle Re-Identification. - Yongbiao Chen; Sheng Zhang; Fangxin Liu; Chenggang Wu; Kaicheng Guo; Zhengwei Qi (IEEE Trans. Intell. Transp. Syst., 2023)

ERA-BS: Boosting the Efficiency of ReRAM-Based PIM Accelerator With Fine-Grained Bit-Level Sparsity. - Fangxin Liu; Wenbo Zhao 005; Zongwu Wang; Yongbiao Chen; Xiaoyao Liang; Li Jiang 002 (IEEE Trans. Computers, 2024)