An intelligent pattern recognition method for machine fault diagnosis. - Linfeng Deng; Rongzhen Zhao (URAI, 2013)

A framework to develop intelligent information system for rotating machinery in a data-driven way. - Rongzhen Zhao; Linfeng Deng; Zhaohui Li (URAI, 2013)

F-LLE algorithm and its application in fault feature extraction. - Rongzhen Zhao; Kunju Shi; Zhaohui Li; Tao Zhang (URAI, 2013)

A method to integrate KSSOMFA and WKNN together on faults identification of rotating machinery. - Xiaoli Zhao; Rongzhen Zhao (URAI, 2016)

A OneM2M-Compliant Stacked Middleware Promoting IoT Research and Development. - Rongzhen Zhao; Litian Wang; Xingzhe Zhang; Yu Zhang; Lizhi Wang; Hongzhao Peng (IEEE Access, 2018)

A New Fault Feature Extraction Method for Rotating Machinery Based on Multiple Sensors. - Feng Miao; Rongzhen Zhao; Xianli Wang; Leilei Jia (Sensors, 2020)

Intelligent fault diagnosis of rolling bearings using a semi-supervised convolutional neural network. - Yaochun Wu; Rongzhen Zhao; Wuyin Jin; Tianjing He; Sencai Ma; Mingkuan Shi (Appl. Intell., 2021)

Learnable Heterogeneous Convolution: Learning both topology and strength. - Rongzhen Zhao; Zhenzhi Wu; Qikun Zhang (Neural Networks, 2021)

Convolution of Convolution: Let Kernels Spatially Collaborate. - Rongzhen Zhao; Jian Li; Zhenzhi Wu (CVPR, 2022)

Intelligent fault diagnosis of rolling bearing based on novel CNN model considering data imbalance. - Ziyang Xing; Rongzhen Zhao; Yaochun Wu; Tianjing He (Appl. Intell., 2022)

Modeling learnable electrical synapse for high precision spatio-temporal recognition. - Zhenzhi Wu; Zhihong Zhang; Huanhuan Gao; Jun Qin; Rongzhen Zhao; Guangshe Zhao; Guoqi Li (Neural Networks, 2022)

Unsupervised structure subdomain adaptation based the Contrastive Cluster Center for bearing fault diagnosis. - Pengfei Chen; Rongzhen Zhao; Tianjing He; Kongyuan Wei; Jianhui Yuan (Eng. Appl. Artif. Intell., 2023)

A novel bearing fault diagnosis method based joint attention adversarial domain adaptation. - Pengfei Chen; Rongzhen Zhao; Tianjing He; Kongyuan Wei; Jianhui Yuan (Reliab. Eng. Syst. Saf., 2023)

Grouped Discrete Representation for Object-Centric Learning. - Rongzhen Zhao; Vivienne Wang; Juho Kannala; Joni Pajarinen (CoRR, 2024)

Multi-Scale Fusion for Object Representation. - Rongzhen Zhao; Vivienne Huiling Wang; Juho Kannala; Joni Pajarinen (ICLR, 2025)

Multimetric hypergraph embedding for dimensionality reduction in rotor fault diagnosis. - Yongfei Zhang; Yuqiao Zheng; Rongzhen Zhao; Linfeng Deng; Mingkuan Shi; Pengfei Chen; Kongyuan Wei (Adv. Eng. Informatics, 2025)

Dimensionality reduction of rolling bearing fault data based on graph-embedded semi-supervised deep auto-encoders. - Wei Kongyuan; Rongzhen Zhao; Haixia Kou; Pengfei Chen; Yongyong Cao; Yuqiao Zheng; Linfeng Deng (Eng. Appl. Artif. Intell., 2025)

Vector-Quantized Vision Foundation Models for Object-Centric Learning. - Rongzhen Zhao; Vivienne Wang; Juho Kannala; Joni Pajarinen (CoRR, 2025)

MetaSlot: Break Through the Fixed Number of Slots in Object-Centric Learning. - Hongjia Liu; Rongzhen Zhao; Haohan Chen; Joni Pajarinen (CoRR, 2025)

Slot Attention with Re-Initialization and Self-Distillation. - Rongzhen Zhao; Yi Zhao 014; Juho Kannala; Joni Pajarinen (CoRR, 2025)

Predicting Video Slot Attention Queries from Random Slot-Feature Pairs. - Rongzhen Zhao; Jian Li; Juho Kannala; Joni Pajarinen (CoRR, 2025)

Smoothing Slot Attention Iterations and Recurrences. - Rongzhen Zhao; Wenyan Yang; Juho Kannala; Joni Pajarinen (CoRR, 2025)