Publications
Jun Chen, Yong Liu, Hao Zhang, Shengnan Hou and Jian Yang. " Propagating asymptotic-estimated gradients for low bitwidth quantized neural networks. " IEEE Journal of Selected Topics in Signal Processing. 2020.
Jun Chen, Liang Liu, Yong Liu and Xianfang Zeng. " A Learning Framework for n-Bit Quantized Neural Networks Toward FPGAs. " IEEE Transactions on Neural Networks and Learning Systems. 2020.
Guanzhong Tian*, Jun Chen*, Xianfang Zeng and Yong Liu. " Pruning by Training: A Novel Deep Neural Network Compression Framework for Image Processing. " IEEE Signal Processing Letters. 2021.
Yuang Liu*, Jun Chen* and Yong Liu. " DCCD: Reducing Neural Network Redundancy via Distillation. " IEEE Transactions on Neural Networks and Learning Systems. 2023.
Jun Chen, Shipeng Bai, Tianxin Huang, Mengmeng Wang, Guanzhong Tian and Yong Liu. " A Data-Free Quantization via Mixed-Precision Compensation without Fine-Tuning. " Pattern Recognition. 2023.
Shipeng Bai*, Jun Chen*, Xintian Shen, Yixuan Qian and Yong Liu. " Unified Data-Free Compression: Pruning and Quantization without Fine-Tuning. " ICCV. 2023.
Bofeng Jiang*, Jun Chen* and Yong Liu. " Single-shot pruning and quantization for hardware-friendly neural network acceleration. " Engineering Applications of Artificial Intelligence. 2023.
Shipeng Bai*, Jun Chen*, Yu Yang and Yong Liu. " Multi-Dimension Compression of Feed-Forward Network in Vision Transformers. " Pattern Recognition Letters. 2023.
Submitted Papers
Awards
First Prize of Zhejiang Province Science and Technology Progress Award in 2021 (2021年浙江省科学技术进步一等奖)