Zhuqing Yuan

Orcid: 0000-0002-1042-9711

According to our database1, Zhuqing Yuan authored at least 12 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Modularized Equalization Architecture With Transformer-Based Integrating Voltage Equalizer for the Series-Connected Battery Pack in Electric Bicycles.
IEEE Trans. Ind. Electron., July, 2023

2022
PACA: A Pattern Pruning Algorithm and Channel-Fused High PE Utilization Accelerator for CNNs.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

A 65-nm Energy-Efficient Interframe Data Reuse Neural Network Accelerator for Video Applications.
IEEE J. Solid State Circuits, 2022

Efficient Neural Networks with Spatial Wise Sparsity Using Unified Importance Map.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

2021
High Area/Energy Efficiency RRAM CNN Accelerator with Pattern-Pruning-Based Weight Mapping Scheme.
Proceedings of the 10th IEEE Non-Volatile Memory Systems and Applications Symposium, 2021

2020
Adaptive Structured Sparse Network for Efficient CNNs with Feature Regularization.
CoRR, 2020

High Area/Energy Efficiency RRAM CNN Accelerator with Kernel-Reordering Weight Mapping Scheme Based on Pattern Pruning.
CoRR, 2020

ADMP: An Adversarial Double Masks Based Pruning Framework For Unsupervised Cross-Domain Compression.
CoRR, 2020

Multi-channel precision-sparsity-adapted inter-frame differential data codec for video neural network processor.
Proceedings of the ISLPED '20: ACM/IEEE International Symposium on Low Power Electronics and Design, 2020

High-Quality Single-Model Deep Video Compression with Frame-Conv3D and Multi-frame Differential Modulation.
Proceedings of the Computer Vision - ECCV 2020, 2020

High PE Utilization CNN Accelerator with Channel Fusion Supporting Pattern-Compressed Sparse Neural Networks.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

A 112-765 GOPS/W FPGA-based CNN Accelerator using Importance Map Guided Adaptive Activation Sparsification for Pix2pix Applications.
Proceedings of the IEEE Asian Solid-State Circuits Conference, 2020


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