Fengzhen Tang - RankMe

35 papers A* 3B 5C 1Journal 23Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An Improved Artificial Potential Field Method With Distributed Representation and Scale-Invariant Path Planning. IEEE Trans. Cogn. Dev. Syst. Fei Song, Yuxiu Shao, Dengyao Jiang, Ziyu Ren, Fengzhen Tang, Yandong Tang, Bailu Si
2026	J	`jnl`	Real-time EEG-based emotion recognition using Riemannian quantification learning. Biomed. Signal Process. Control. Bo Lv, Yaobo Yu, Fanbo Zhuo, Fengzhen Tang
2025	J	`jnl`	A Collaborative Mapping System for a Brain-Inspired SLAM. IEEE Internet Things J. Hangpiao Zhao, Tao Li, Zhihui Zhang, Fengzhen Tang
2025	J	`jnl`	A hierarchical Bayesian inference model for volatile multivariate exponentially distributed signals. Frontiers Comput. Neurosci. Changbo Zhu, Ke Zhou, Fengzhen Tang, Yandong Tang, Xiaoli Li, Bailu Si
2025	J	`jnl`	Robust Soft LVQ With LEML for SPD Matrices. IEEE Trans. Emerg. Top. Comput. Intell. Fengzhen Tang, Xiaocheng Zhang
2024	B	`conf`	Addressing Intermediate Verification Latency in Online Learning Through Immediate Pseudo-labeling and Oriented Synthetic Correction. IJCNN Zixin Zhong, Liyan Song, Fengzhen Tang, Bo Yuan
2024	—	`conf`	Time Window Optimization for Riemannian Geometry-based Motor Imagery EEG Classification. EMBC Fanbo Zhuo, Bo Lv, Fengzhen Tang
2023	J	`jnl`	Dimension selection for EEG classification in the SPD Riemannian space based on PSO. Knowl. Based Syst. Zirui Zhang, Yinan Guo, Fengzhen Tang
2023	J	`jnl`	Generalized Learning Vector Quantization With Log-Euclidean Metric Learning on Symmetric Positive-Definite Manifold. IEEE Trans. Cybern. Fengzhen Tang, Peter Tino, Haibin Yu
2023	J	`jnl`	Knowledge-based hybrid connectionist models for morphologic reasoning. Mach. Vis. Appl. Kai He, Wenxue Wang, Gang Li, Peng Yu, Fengzhen Tang, Ning Xi, Lianqing Liu
2023	B	`conf`	Prototype based linear sub-manifold learning. IJCNN Mengling Fan, Fengzhen Tang, Xingang Zhao
2023	J	`jnl`	Vibration optimization of cantilevered bistable composite shells based on machine learning. Eng. Appl. Artif. Intell. Chenchen Wu, Ruming Zhang, Fengzhen Tang, Mengling Fan
2022	J	`jnl`	A transfer weighted extreme learning machine for imbalanced classification. Int. J. Intell. Syst. Yinan Guo, Botao Jiao, Ying Tan, Pei Zhang, Fengzhen Tang
2022	J	`jnl`	Nonstationary fuzzy neural network based on FCMnet clustering and a modified CG method with Armijo-type rule. Inf. Sci. Bingjie Zhang, Xiaoling Gong, Jian Wang, Fengzhen Tang, Kai Zhang, Wei Wu
2022	J	`jnl`	Riemannian dynamic generalized space quantization learning. Pattern Recognit. Mengling Fan, Fengzhen Tang, Yinan Guo, Xingang Zhao
2021	J	`jnl`	A novel oversampling technique based on the manifold distance for class imbalance learning. Int. J. Bio Inspired Comput. Yinan Guo, Botao Jiao, Lingkai Yang, Jian Cheng, Shengxiang Yang, Fengzhen Tang
2021	J	`jnl`	Feature selection with kernelized multi-class support vector machine. Pattern Recognit. Yinan Guo, Zirui Zhang, Fengzhen Tang
2021	J	`jnl`	Generalized Learning Riemannian Space Quantization: A Case Study on Riemannian Manifold of SPD Matrices. IEEE Trans. Neural Networks Learn. Syst. Fengzhen Tang, Mengling Fan, Peter Tiño
2021	J	`jnl`	Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices. CoRR Fengzhen Tang, Haifeng Feng, Peter Tiño, Bailu Si, Daxiong Ji
2021	J	`jnl`	Probabilistic learning vector quantization on manifold of symmetric positive definite matrices. Neural Networks Fengzhen Tang, Haifeng Feng, Peter Tino, Bailu Si, Daxiong Ji
2020	J	`jnl`	NeuroBayesSLAM: Neurobiologically inspired Bayesian integration of multisensory information for robot navigation. Neural Networks Taiping Zeng, Fengzhen Tang, Daxiong Ji, Bailu Si
2019	J	`jnl`	Learning joint space-time-frequency features for EEG decoding on small labeled data. Neural Networks Dongye Zhao, Fengzhen Tang, Bailu Si, Xisheng Feng
2019	J	`jnl`	Scan registration for underwater mechanical scanning imaging sonar using symmetrical Kullback-Leibler divergence. J. Electronic Imaging Min Jiang, Sanming Song, Fengzhen Tang, Yiping Li, Jian Liu, Xisheng Feng
2019	B	`conf`	Unsupervised Feature Learning for Visual Place Recognition in Changing Environments. IJCNN Dongye Zhao, Bailu Si, Fengzhen Tang
2018	J	`jnl`	Group feature selection with multiclass support vector machine. Neurocomputing Fengzhen Tang, Lukás Adam, Bailu Si
2017	A*	`conf`	A prey-predator model for efficient robot tracking. ICRA Fengzhen Tang, Bailu Si, Daxiong Ji
2017	—	`conf`	Model learning based on grid cell representations. ROBIO Guanwen Huang, Bailu Si, Fengzhen Tang
2017	J	`jnl`	Ordinal regression based on learning vector quantization. Neural Networks Fengzhen Tang, Peter Tiño
2015	—	`—`	Kernel methods for time series data. Fengzhen Tang
2015	A*	`conf`	Model Metric Co-Learning for Time Series Classification. IJCAI Huanhuan Chen, Fengzhen Tang, Peter Tiño, Anthony G. Cohn, Xin Yao
2015	J	`jnl`	The Benefits of Modeling Slack Variables in SVMs. Neural Comput. Fengzhen Tang, Peter Tiño, Pedro Antonio Gutiérrez, Huanhuan Chen
2014	B	`conf`	Learning the deterministically constructed Echo State Networks. IJCNN Fengzhen Tang, Peter Tiño, Huanhuan Chen
2014	B	`conf`	Support Vector Ordinal Regression using Privileged Information. ESANN Fengzhen Tang, Peter Tiño, Pedro Antonio Gutiérrez, Huanhuan Chen
2013	A*	`conf`	Model-based kernel for efficient time series analysis. KDD Huanhuan Chen, Fengzhen Tang, Peter Tiño, Xin Yao
2010	C	`conf`	Liver cancer identification based on PSO-SVM model. ICARCV Huiyan Jiang, Fengzhen Tang, Xiyue Zhang