山东大学教师主页隋青美论文成果中文主页

个人信息

隋青美

性别：女
在职信息：在职

个人信息 Personal information

在职信息：在职所在单位：控制科学与工程学院入职时间：1986-07-01 所属院系：控制科学与工程学院

论文成果

中文主页 - 科学研究 - 论文成果

[1] 王正方. A Pavement Crack Registration and Change Identification Method Based on Unsupervised Deep Neural Network. IEEE Transactions on Intelligent Transportation Systems, 26, 757, 2025.
[2] 魏钧涛. Probabilistic diagnostic imaging method based on the difference between the arrival moments of ultrasonic guided wave signals. Measurement, 116083, 2025.
[3] 王正方. A Semisupervised Deep Learning Method for Ground Penetrating Radar Data Inversion and Concrete Subsurface Defect Imaging. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING , 63, 2025.
[4] 张法业. Novel sparse auto-encoder framework with pseudo-labeled reinforcement for cross domain fault diagnosis with imbalanced samples. MEASUREMENT SCIENCE AND TECHNOLOGY, 36, 2024.
[5] 魏钧涛. Modified reconstruction algorithm for probabilistic inspection of damage based on damaged virtual sensing paths. Measurement, 218, 2023.
[6] 叶呈龙. Novel cross-domain fault diagnosis method based on model-agnostic meta-learning embedded in adaptive threshold network. Measurement, 113677, 2023.
[7] 刘福政. Fault diagnosis of rolling bearing combining improved AWSGMD-CP and ACO-ELM model. Measurement, 112531, 2023.
[8] 刘福政. Structural discrepancy and domain adversarial fusion network for cross-domain fault diagnosis. ADVANCED ENGINEERING INFORMATICS, 102217, 2023.
[9] 徐静. Deep-Neural-Network-Based Subsurface Defect Identification Method for Multi-Polarimetric Ground Penetrating Radar Data. IEEE Sensors Journal, 24, 7165, 2024.
[10] 季银涛. Deep Neural Network-Based Permittivity Inversions for Ground Penetrating Radar Data. IEEE Sensors Journal, 21, 8172, 2021.

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