Jie Ding

Orcid: 0000-0002-5637-228X

Affiliations:
  • Fudan University, School of Information Science and Engineering, Electronic Engineering Department, Research Center of Smart Networks and Systems, Shanghai, China
  • Agency for Science, Technology and Research, A*STAR, Institute for Infocomm Research, I2R, Singapore (2018-2019)
  • Nanyang Technological University, Singapore (PhD 2018)


According to our database1, Jie Ding authored at least 14 papers between 2014 and 2024.

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Bibliography

2024
Target Controllability of Multiplex Networks With Weighted Interlayer Edges.
IEEE Trans. Netw. Sci. Eng., 2024

2023
MHGAN: A Multi-Headed Generative Adversarial Network for Underwater Sonar Image Super-Resolution.
IEEE Trans. Geosci. Remote. Sens., 2023

2021
Target Controllability in Multilayer Networks via Minimum-Cost Maximum-Flow Method.
IEEE Trans. Neural Networks Learn. Syst., 2021

Key Nodes Selection in Controlling Complex Networks via Convex Optimization.
IEEE Trans. Cybern., 2021

2020
Sparsity-Inspired Optimal Topology Control of Complex Networks.
IEEE Trans. Netw. Sci. Eng., 2020

Smartphone Sensor-Based Human Activity Recognition Using Feature Fusion and Maximum Full a Posteriori.
IEEE Trans. Instrum. Meas., 2020

A Computational Framework for Iceberg and Ship Discrimination: Case Study on Kaggle Competition.
IEEE Access, 2020

ID Preserving Face Super-Resolution Generative Adversarial Networks.
IEEE Access, 2020

2019
Minimum Cost Control of Directed Networks With Selectable Control Inputs.
IEEE Trans. Cybern., 2019

Controlling Directed Networks With Evolving Topologies.
IEEE Trans. Control. Netw. Syst., 2019

A Multi-channel Deep Learning Approach for Segmentation of the Left Ventricular Endocardium from Cardiac Images.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

2017
Optimal control of weighted networks based on node connection strength.
Proceedings of the 26th IEEE International Symposium on Industrial Electronics, 2017

2016
Locality sensitive batch feature extraction for high-dimensional data.
Neurocomputing, 2016

2014
Min-max discriminant analysis based on gradient method for feature extraction.
Proceedings of the 13th International Conference on Control Automation Robotics & Vision, 2014


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