Shuo Zhang

Orcid: 0000-0002-7427-1933

Affiliations:
  • Zhengzhou University, School of Information Engineering, Cooperative Innovation Center of Internet Healthcare, China


According to our database1, Shuo Zhang authored at least 13 papers between 2019 and 2025.

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

Timeline

Legend:

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Bibliography

2025
Perceptual Screen Content Image Hashing Using Adaptive Texture and Shape Features.
IEEE Signal Process. Lett., 2025

Predicting the progression of mild cognitive impairment based on fine-grained and spatiotemporal features of MRI.
Biomed. Signal Process. Control., 2025

2024
Gate Feature Interaction Network for Relation Prediction in Knowledge Graph.
Data Intell., 2024

Improving Large Models with Small models: Lower Costs and Better Performance.
CoRR, 2024

Data Shunt: Collaboration of Small and Large Models for Lower Costs and Better Performance.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Multi-view feature representation and fusion for drug-drug interactions prediction.
BMC Bioinform., December, 2023

ControlRetriever: Harnessing the Power of Instructions for Controllable Retrieval.
CoRR, 2023

2022
Interpretability Analysis of One-Year Mortality Prediction for Stroke Patients Based on Deep Neural Network.
IEEE J. Biomed. Health Informatics, 2022

Interpretable CNN for ischemic stroke subtype classification with active model adaptation.
BMC Medical Informatics Decis. Mak., 2022

2021
A Multi-granularity Fusion Neural Network Model for Medical Question Classification.
Proceedings of the 7th IEEE International Conference on Cloud Computing and Intelligent Systems, 2021

TSC-MI: A Temporal Spatial Convolution Neural Network Fused with Mutual Information for Motor Imagery Based EEG Classification.
Proceedings of the Brain Informatics - 14th International Conference, 2021

2020
Multimodal Sleep Signals-Based Automated Sleep Arousal Detection.
IEEE Access, 2020

2019
D-STC: Deep learning with spatio-temporal constraints for train drivers detection from videos.
Pattern Recognit. Lett., 2019


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