Zhongming Fu

Orcid: 0000-0003-3041-6990

According to our database1, Zhongming Fu authored at least 17 papers between 2017 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
KMHCR: A Key-Controlled Signal-Domain Transformation for 5G IoT Security.
J. Signal Process. Syst., June, 2026

GraphDelta: A distributed incremental framework for efficient dynamic graph computing in edge intelligence.
J. Syst. Archit., 2026

2025
Optimizing Data Locality by Integrating Intermediate Data Partitioning and Reduce Task Scheduling in Spark Framework.
IEEE Trans. Parallel Distributed Syst., November, 2025

Optimization of fault tolerance for iterative graph algorithm in spark GraphX based on high performance computing cluster.
CCF Trans. High Perform. Comput., October, 2025

UM-Mamba: An efficient U-network with medical visual state space for medical image segmentation.
Comput. Vis. Image Underst., 2025

2024
Improving Data Locality of Tasks by Executor Allocation in Spark Computing Environment.
IEEE Trans. Cloud Comput., 2024

An Enhanced U-Network by Combining PPM and CBAM for Medical Image Segmentation.
IEEE Access, 2024

2023
Optimizing data locality by executor allocation in spark computing environment.
Comput. Sci. Inf. Syst., 2023

PCU-Net: An enhanced U-network by combining PPM and CBAM for Medical Image Segmentation.
Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems, 2023

2022
IncGraph: An Improved Distributed Incremental Graph Computing Model and Framework Based on Spark GraphX.
IEEE Trans. Knowl. Data Eng., 2022

Optimizing Speculative Execution in Spark Heterogeneous Environments.
IEEE Trans. Cloud Comput., 2022

Cross-domain Resemblance Detection based on Meta-learning for Cloud Storage.
Proceedings of the IEEE International Performance, 2022

2021
Optimizing Data Locality by Executor Allocation in Reduce Stage for Spark Framework.
Proceedings of the Parallel and Distributed Computing, Applications and Technologies, 2021

2020
An Optimal Locality-Aware Task Scheduling Algorithm Based on Bipartite Graph Modelling for Spark Applications.
IEEE Trans. Parallel Distributed Syst., 2020

ImRP: A Predictive Partition Method for Data Skew Alleviation in Spark Streaming Environment.
Parallel Comput., 2020

2019
i2Graph: An Incremental Iterative Computation Model for Large Scale Dynamic Graphs.
Proceedings of the 2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, 2019

2017
A Parallel Conditional Random Fields Model Based on Spark Computing Environment.
J. Grid Comput., 2017


  Loading...