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2020 – today
- 2024
[i4]Rongzhen Zhao, Vivienne Wang, Juho Kannala, Joni Pajarinen:
Grouped Discrete Representation Guides Object-Centric Learning. CoRR abs/2407.01726 (2024)- [i3]Rongzhen Zhao, Vivienne Wang, Juho Kannala, Joni Pajarinen:
Organized Grouped Discrete Representation for Object-Centric Learning. CoRR abs/2409.03553 (2024) - [i2]Rongzhen Zhao, Vivienne Wang, Juho Kannala, Joni Pajarinen:
Multi-Scale Fusion for Object Representation. CoRR abs/2410.01539 (2024) - 2023
- [j8]Pengfei Chen, Rongzhen Zhao
, Tianjing He, Kongyuan Wei, Jianhui Yuan:
Unsupervised structure subdomain adaptation based the Contrastive Cluster Center for bearing fault diagnosis. Eng. Appl. Artif. Intell. 122: 106141 (2023) - [j7]Pengfei Chen, Rongzhen Zhao, Tianjing He, Kongyuan Wei, Jianhui Yuan:
A novel bearing fault diagnosis method based joint attention adversarial domain adaptation. Reliab. Eng. Syst. Saf. 237: 109345 (2023) - [i1]Rongzhen Zhao, Zhenzhi Wu, Qikun Zhang:
Learnable Heterogeneous Convolution: Learning both topology and strength. CoRR abs/2301.05440 (2023) - 2022
- [j6]Ziyang Xing, Rongzhen Zhao, Yaochun Wu, Tianjing He:
Intelligent fault diagnosis of rolling bearing based on novel CNN model considering data imbalance. Appl. Intell. 52(14): 16281-16293 (2022) - [j5]Zhenzhi Wu, Zhihong Zhang, Huanhuan Gao, Jun Qin, Rongzhen Zhao, Guangshe Zhao, Guoqi Li:
Modeling learnable electrical synapse for high precision spatio-temporal recognition. Neural Networks 149: 184-194 (2022) - [c5]Rongzhen Zhao, Jian Li, Zhenzhi Wu:
Convolution of Convolution: Let Kernels Spatially Collaborate. CVPR 2022: 641-650 - 2021
- [j4]Yaochun Wu, Rongzhen Zhao, Wuyin Jin, Tianjing He, Sencai Ma, Mingkuan Shi:
Intelligent fault diagnosis of rolling bearings using a semi-supervised convolutional neural network. Appl. Intell. 51(4): 2144-2160 (2021) - [j3]Rongzhen Zhao, Zhenzhi Wu, Qikun Zhang:
Learnable Heterogeneous Convolution: Learning both topology and strength. Neural Networks 141: 270-280 (2021) - 2020
- [j2]Feng Miao, Rongzhen Zhao, Xianli Wang, Leilei Jia:
A New Fault Feature Extraction Method for Rotating Machinery Based on Multiple Sensors. Sensors 20(6): 1713 (2020)
2010 – 2019
- 2018
- [j1]Rongzhen Zhao, Litian Wang, Xingzhe Zhang, Yu Zhang, Lizhi Wang, Hongzhao Peng:
A OneM2M-Compliant Stacked Middleware Promoting IoT Research and Development. IEEE Access 6: 63546-63559 (2018) - 2016
- [c4]Xiaoli Zhao, Rongzhen Zhao:
A method to integrate KSSOMFA and WKNN together on faults identification of rotating machinery. URAI 2016: 675-680 - 2013
- [c3]Rongzhen Zhao, Linfeng Deng, Zhaohui Li:
A framework to develop intelligent information system for rotating machinery in a data-driven way. URAI 2013: 182-186 - [c2]Linfeng Deng, Rongzhen Zhao:
An intelligent pattern recognition method for machine fault diagnosis. URAI 2013: 187-192 - [c1]Rongzhen Zhao, Kunju Shi, Zhaohui Li, Tao Zhang:
F-LLE algorithm and its application in fault feature extraction. URAI 2013: 418-422
Coauthor Index
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