Ming Yu

Orcid: 0000-0002-4880-6543

Affiliations:
  • Academy of Military Sciences, Institute of Medical Support, Tianjin, China
  • National Biological Protection Engineering Centre, Institute of Medical Equipment, Tianjin, China


According to our database1, Ming Yu authored at least 13 papers between 2016 and 2025.

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

Timeline

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Bibliography

2025
Research on Robust Measurement Method of Heart Rate Using Remote Photoplethysmography Based on Adversarial Learning Network With High and Low Frequency Features.
IEEE Trans. Circuits Syst. Video Technol., June, 2025

Multi-dimensional spatial pruning for remote sensing image scene classification.
Digit. Signal Process., 2025

Adversarial learning network for recovering rPPG signals from low-resolution images for remote heart rate measurement.
Biomed. Signal Process. Control., 2025

2024
Classification and Location of Cerebral Hemorrhage Points Based on SEM and SSA-GA-BP Neural Network.
IEEE Trans. Instrum. Meas., 2024

2023
Developing and evaluating a machine-learning-based algorithm to predict the incidence and severity of ARDS with continuous non-invasive parameters from ordinary monitors and ventilators.
Comput. Methods Programs Biomed., March, 2023

2022
A machine learning method for predicting the probability of MODS using only non-invasive parameters.
Comput. Methods Programs Biomed., 2022

An interpretable deep learning algorithm for dynamic early warning of posttraumatic hemorrhagic shock based on noninvasive parameter.
Biomed. Signal Process. Control., 2022

2021
A machine learning method for acute hypotensive episodes prediction using only non-invasive parameters.
Comput. Methods Programs Biomed., 2021

A novel approach to estimate blood pressure of blood loss continuously based on stacked auto-encoder neural networks.
Biomed. Signal Process. Control., 2021

2020
A machine learning approach for mortality prediction only using non-invasive parameters.
Medical Biol. Eng. Comput., 2020

PGMM - Pre-Trained Gaussian Mixture Model Based Convolution Neural Network for Electroencephalography Imagery Analysis.
IEEE Access, 2020

2017
A method to differentiate between ventricular fibrillation and asystole during chest compressions using artifact-corrupted ECG alone.
Comput. Methods Programs Biomed., 2017

2016
A new method to detect ventricular fibrillation from CPR artifact-corrupted ECG based on the ECG alone.
Biomed. Signal Process. Control., 2016


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