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Te Han
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2020 – today
- 2025
- [j32]Yuzeng Chen, Qiangqiang Yuan, Yuqi Tang, Yi Xiao, Jiang He, Te Han, Zhenqi Liu, Liangpei Zhang:
SSTtrack: A unified hyperspectral video tracking framework via modeling spectral-spatial-temporal conditions. Inf. Fusion 114: 102658 (2025) - 2024
- [j31]Te Han, Yuqi Tang
, Bin Zou, Huihui Feng:
Unsupervised multimodal change detection based on adaptive optimization of structured graph. Int. J. Appl. Earth Obs. Geoinformation 126: 103630 (2024) - [j30]Chuge Wu
Bearing fault diagnosis using Gradual Conditional Domain Adversarial Network. Appl. Soft Comput. 158: 111580 (2024) - [j29]Xiaochen Zhang
Trustworthy Diagnostics With Out-of-Distribution Detection: A Novel Max-Consistency and Min-Similarity Guided Deep Ensembles for Uncertainty Estimation. IEEE Internet Things J. 11(13): 23055-23067 (2024) - [j28]Zhonghao Chang
Photovoltaic Cell Anomaly Detection Enabled by Scale Distribution Alignment Learning and Multiscale Linear Attention Framework. IEEE Internet Things J. 11(16): 27816-27827 (2024) - [j27]Yuqi Tang
Enhanced Graph Structure Representation for Unsupervised Heterogeneous Change Detection. Remote. Sens. 16(4): 721 (2024) - [j26]Yuqi Tang
Iterative Optimization-Enhanced Contrastive Learning for Multimodal Change Detection. Remote. Sens. 16(19): 3624 (2024) - [j25]Yongbo Cheng, Junheng Qv, Ke Feng, Te Han
A Bayesian adversarial probsparse Transformer model for long-term remaining useful life prediction. Reliab. Eng. Syst. Saf. 248: 110188 (2024) - [j24]Te Han
SDC-GAE: Structural Difference Compensation Graph Autoencoder for Unsupervised Multimodal Change Detection. IEEE Trans. Geosci. Remote. Sens. 62: 1-16 (2024) - [j23]Xiaoyu Luo
FFT-Trans: Enhancing Robustness in Mechanical Fault Diagnosis With Fourier Transform-Based Transformer Under Noisy Conditions. IEEE Trans. Instrum. Meas. 73: 1-12 (2024) - [j22]Ning Zhu
An Adversarial Training Framework Based on Unsupervised Feature Reconstruction Constraints for Crystalline Silicon Solar Cells Anomaly Detection. IEEE Trans. Instrum. Meas. 73: 1-13 (2024) - 2023
- [j21]Zhe Li
The Performance Analysis of SPMA Protocol in High Speed Mobile Ad Hoc Network. IEEE Access 11: 23485-23494 (2023) - [j20]Wenzhen Xie, Te Han
A unified out-of-distribution detection framework for trustworthy prognostics and health management in renewable energy systems. Eng. Appl. Artif. Intell. 125: 106707 (2023) - [j19]Te Han
Semi-supervised adversarial discriminative learning approach for intelligent fault diagnosis of wind turbine. Inf. Sci. 648: 119496 (2023) - [j18]Zhe Wang
Attention-aware temporal-spatial graph neural network with multi-sensor information fusion for fault diagnosis. Knowl. Based Syst. 278: 110891 (2023) - [j17]Taotao Zhou
An uncertainty-informed framework for trustworthy fault diagnosis in safety-critical applications. Reliab. Eng. Syst. Saf. 229: 108865 (2023) - [j16]Huixing Meng
Long short-term memory network with Bayesian optimization for health prognostics of lithium-ion batteries based on partial incremental capacity analysis. Reliab. Eng. Syst. Saf. 236: 109288 (2023) - [j15]Shicheng Pei
Time-Efficient Neural Architecture Search for Autonomous Underwater Vehicle Fault Diagnosis. IEEE Trans. Instrum. Meas. 72: 1-11 (2023) - [c5]Yifan Zhou, Tian-Jian Luo, Xiaochen Zhang, Te Han:
Spatial Feature Regularization and Label Decoupling Based Cross-Subject Motor Imagery EEG Decoding. PRCV (13) 2023: 407-423 - 2022
- [j14]Yuzeng Chen
RAMC: A Rotation Adaptive Tracker with Motion Constraint for Satellite Video Single-Object Tracking. Remote. Sens. 14(13): 3108 (2022) - [j13]Taotao Zhou
Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework. Reliab. Eng. Syst. Saf. 224: 108525 (2022) - [j12]Te Han
Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles. Reliab. Eng. Syst. Saf. 226: 108648 (2022) - [j11]Yuzeng Chen
Single Object Tracking in Satellite Videos: A Correlation Filter-Based Dual-Flow Tracker. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15: 6687-6698 (2022) - [j10]Min Qian
Positive-Unlabeled Learning-Based Hybrid Deep Network for Intelligent Fault Detection. IEEE Trans. Ind. Informatics 18(7): 4510-4519 (2022) - [c4]Te Han, Yuqi Tang, Yuzeng Chen:
Heterogeneous Image Change Detection Based on Two-Stage Joint Feature Learning. IGARSS 2022: 3215-3218 - [c3]Zhenyu Deng, Te Han, Ruonan Liu, Fengyao Zhi:
A fault diagnosis method in industrial processes with integrated feature space and optimized random forest. ISIE 2022: 1170-1173 - 2021
- [j9]Te Han
Deep transfer learning with limited data for machinery fault diagnosis. Appl. Soft Comput. 103: 107150 (2021) - [j8]Te Han
Change Detection for Heterogeneous Remote Sensing Images with Improved Training of Hierarchical Extreme Learning Machine (HELM). Remote. Sens. 13(23): 4918 (2021) - [j7]Xin Li
Multi-sensor gearbox fault diagnosis by using feature-fusion covariance matrix and multi-Riemannian kernel ridge regression. Reliab. Eng. Syst. Saf. 216: 108018 (2021) - [j6]Te Han
A Hybrid Generalization Network for Intelligent Fault Diagnosis of Rotating Machinery Under Unseen Working Conditions. IEEE Trans. Instrum. Meas. 70: 1-11 (2021)
2010 – 2019
- 2019
- [j5]Te Han
A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults. Knowl. Based Syst. 165: 474-487 (2019) - 2018
- [j4]Te Han
Comparison of random forest, artificial neural networks and support vector machine for intelligent diagnosis of rotating machinery. Trans. Inst. Meas. Control 40(8): 2681-2693 (2018) - [i1]Te Han, Chao Liu, Wenguang Yang, Dongxiang Jiang:
Deep Transfer Network with Joint Distribution Adaptation: A New Intelligent Fault Diagnosis Framework for Industry Application. CoRR abs/1804.07265 (2018) - 2017
- [j3]Xiaochen Zhang
Rotating Machinery Fault Diagnosis for Imbalanced Data Based on Fast Clustering Algorithm and Support Vector Machine. J. Sensors 2017: 8092691:1-8092691:15 (2017) - [j2]Te Han
Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition. Sensors 17(4): 689 (2017) - 2013
- [c2]Bohan Wu, Weixin Gai, Te Han:
A novel frequency search algorithm to achieve fast locking without phase tracking in ADPLL. ISCAS 2013: 2464-2467 - [c1]Te Han, Weixin Gai:
A 2.7-GHz digitally-controlled ring oscillator with supply sensitivity of 0.0014%-fDCO/1%-VDD using digital current-regulated tuning. ISCAS 2013: 2690-2693
1970 – 1979
- 1979
- [j1]Te Han:
Source coding with cross observations at the encoders (Corresp.). IEEE Trans. Inf. Theory 25(3): 360-361 (1979)
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