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Guoqing Mu
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2020 – today
- 2024
- [j8]Jingxiang Liu
, Weimin Zhu
A concise subspace projection based meta-learning method for fast modeling and monitoring in multi-grade semiconductor process. Comput. Ind. Eng. 188: 109914 (2024) - [j7]Zhong Qu, Ming Li, Bin Yuan, Guoqing Mu:
A method of hybrid dilated and global convolution networks for pavement crack detection. Multim. Syst. 30(4): 210 (2024) - [j6]Shuai He
Data-Driven Power Prediction for Proton Exchange Membrane Fuel Cell Reactor Systems. Sensors 24(18): 6120 (2024) - 2023
- [j5]Jingxiang Liu
Tensor slow feature analysis and its applications for batch process monitoring. Comput. Chem. Eng. 173: 108207 (2023) - [j4]Jingxiang Liu
Just-In-Time Learning Based Functional Spectral Data Modeling for In-Situ Measurement of Slurry Component Concentrations via Infrared Spectroscopy. IEEE Trans. Instrum. Meas. 72: 1-10 (2023) - 2022
- [j3]Guoqing Mu
Developing a Conditional Variational Autoencoder to Guide Spectral Data Augmentation for Calibration Modeling. IEEE Trans. Instrum. Meas. 71: 1-8 (2022) - [j2]Guoqing Mu
Variational PLS-Based Calibration Model Building With Semi-Supervised Learning for Moisture Measurement During Fluidized Bed Drying by NIR Spectroscopy. IEEE Trans. Instrum. Meas. 71: 1-13 (2022) - [c1]Jingxiang Liu, Junhui Chen, Guoqing Mu
Tensor Slow Feature Analysis for Monitoring Batch Process. ASCC 2022: 643-648 - 2021
- [j1]Guoqing Mu
Semi-Supervised Learning-Based Calibration Model Building of NIR Spectroscopy for In Situ Measurement of Biochemical Processes Under Insufficiently and Inaccurately Labeled Samples. IEEE Trans. Instrum. Meas. 70: 1-12 (2021)
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