Xingchen Dong

Orcid: 0009-0000-4930-0766

According to our database1, Xingchen Dong authored at least 12 papers between 2014 and 2025.

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

Timeline

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Bibliography

2025
CNN-Informer: A hybrid deep learning model for seizure detection on long-term EEG.
Neural Networks, 2025

2024
Epileptic Seizure Prediction Using Spatiotemporal Feature Fusion on EEG.
Int. J. Neural Syst., August, 2024

Epileptic Seizure Detection with an End-to-End Temporal Convolutional Network and Bidirectional Long Short-Term Memory Model.
Int. J. Neural Syst., March, 2024

Automatic Seizure Detection Based on Stockwell Transform and Transformer.
Sensors, 2024

End-to-end model for automatic seizure detection using supervised contrastive learning.
Eng. Appl. Artif. Intell., 2024

Deep learning based automatic seizure prediction with EEG time-frequency representation.
Biomed. Signal Process. Control., 2024

An Efficient Growth Optimizer with Adaptive Parameters and Targeted Stochastic Mutation Strategies for Global Optimization.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024

2023
Epileptic Seizure Prediction Using Attention Augmented Convolutional Network.
Int. J. Neural Syst., November, 2023

2017
A DFT Calculation of Fluoride-Doped TiO<sub>2</sub> Nanotubes for Detecting SF<sub>6</sub> Decomposition Components.
Sensors, 2017

2016
Investigation of Gas-Sensing Property of Acid-Deposited Polyaniline Thin-Film Sensors for Detecting H<sub>2</sub>S and SO<sub>2</sub>.
Sensors, 2016

2015
Analysis of the Sensitivity of K-Type Molecular Sieve-Deposited MWNTs for the Detection of SF6 Decomposition Gases under Partial Discharge.
Sensors, 2015

2014
Gas Sensitivity and Sensing Mechanism Studies on Au-Doped TiO<sub>2</sub> Nanotube Arrays for Detecting SF<sub>6</sub> Decomposed Components.
Sensors, 2014


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