Zhizhe Lin

Orcid: 0000-0002-0088-7241

According to our database1, Zhizhe Lin authored at least 15 papers between 2017 and 2025.

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

Timeline

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Links

On csauthors.net:

Bibliography

2025
MSACN-LSTM: A multivariate time series prediction hybrid network model for extracting spatial features at multiple time scales.
Int. J. Mach. Learn. Cybern., August, 2025

JointSTNet: Joint Pre-Training for Spatial-Temporal Traffic Forecasting.
IEEE Trans. Consumer Electron., May, 2025

Learning From AI-Generated Annotations for Medical Image Segmentation.
IEEE Trans. Consumer Electron., February, 2025

Multi-Scale Cross-Dimensional Attention Network for Gland Segmentation.
IEEE Signal Process. Lett., 2025

Two-way heterogeneity model for dynamic spatiotemporal traffic flow prediction.
Knowl. Based Syst., 2025

2024
A noise-immune and attention-based multi-modal framework for short-term traffic flow forecasting.
Soft Comput., March, 2024

Dynamic spatial aware graph transformer for spatiotemporal traffic flow forecasting.
Knowl. Based Syst., 2024

Overlapping cytoplasms segmentation via constrained multi-shape evolution for cervical cancer screening.
Artif. Intell. Medicine, 2024

2023
Error-distribution-free kernel extreme learning machine for traffic flow forecasting.
Eng. Appl. Artif. Intell., 2023

SAE-SV: A Stacked-AutoEncoder and Soft Voting Joint Approach Based on Small Dataset with High Dimensions for Inhibitory Potency Prediction.
Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science, 2023

2022
PSFNet: A Deep Learning Network for Fake Passport Detection.
IEEE Access, 2022

2021
Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus by Deep Learning Enhanced Magnetic Resonance Spectroscopy.
J. Medical Imaging Health Informatics, 2021

A Noise-Immune Boosting Framework for Short-Term Traffic Flow Forecasting.
Complex., 2021

2017
δ-agree AdaBoost stacked autoencoder for short-term traffic flow forecasting.
Neurocomputing, 2017

Quantitative analysis of patients with celiac disease by video capsule endoscopy: A deep learning method.
Comput. Biol. Medicine, 2017


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