Jing Zhu

Orcid: 0000-0003-3047-287X

Affiliations:
  • Lanzhou University, Gansu Provincial Key Laboratory of Wearable Computing, China


According to our database1, Jing Zhu authored at least 23 papers between 2016 and 2024.

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

Timeline

Legend:

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Online presence:

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Bibliography

2024
Achieving EEG-based depression recognition using Decentralized-Centralized structure.
Biomed. Signal Process. Control., 2024

2023
ChatGPT for Computational Social Systems: From Conversational Applications to Human-Oriented Operating Systems.
IEEE Trans. Comput. Soc. Syst., April, 2023

Mutual Information Based Fusion Model (MIBFM): Mild Depression Recognition Using EEG and Pupil Area Signals.
IEEE Trans. Affect. Comput., 2023

EEG-Based Depression Recognition Using Convolutional Neural Network with FFT and EMD.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Attention Fusion and Abnormal Brain Topology Neural Network for Mild Depression Recognition.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022
Content-based multiple evidence fusion on EEG and eye movements for mild depression recognition.
Comput. Methods Programs Biomed., 2022

EEG based depression recognition using improved graph convolutional neural network.
Comput. Biol. Medicine, 2022

Hybrid fusion model based on DBN and secondary classifier: Multimodal mild depression recognition using EEG and eye movement.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021
Federated Control: Toward Information Security and Rights Protection.
IEEE Trans. Comput. Soc. Syst., 2021

2020
MODMA dataset: a Multi-model Open Dataset for Mental-disorder Analysis.
CoRR, 2020

Attention Bias in Emotional Conflict in Major Depression Disorder: An Eye Tracking Study.
Proceedings of the 22nd IEEE International Conference on E-health Networking, 2020

A functional network study of patients with mild depression based on source location.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

EEG-based mild depression recognition using multi-kernel convolutional and spatial-temporal Feature.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019
EEG-based mild depression recognition using convolutional neural network.
Medical Biol. Eng. Comput., 2019

Depression recognition using machine learning methods with different feature generation strategies.
Artif. Intell. Medicine, 2019

Multimodal Mild Depression Recognition Based on EEG-EM Synchronization Acquisition Network.
IEEE Access, 2019

Multivariate Pattern Analysis of EEG-Based Functional Connectivity: A Study on the Identification of Depression.
IEEE Access, 2019

Toward Depression Recognition Using EEG and Eye Tracking: An Ensemble Classification Model CBEM.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018
Attentional bias in MDD: ERP components analysis and classification using a dot-probe task.
Comput. Methods Programs Biomed., 2018

A Study on Depression Detection Using Eye Tracking.
Proceedings of the Human Centered Computing - 4th International Conference, 2018

Resting State EEG Based Depression Recognition Research Using Deep Learning Method.
Proceedings of the Brain Informatics - International Conference, 2018

2017
A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering.
Complex., 2017

2016
Exploring User Mobile Shopping Activities Based on Characteristic of Eye-Tracking.
Proceedings of the Human Centered Computing - Second International Conference, 2016


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