Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Probabilistic learning vector quantization on manifold of symmetric positive definite matrices.

F. Tang, H. Feng, P. Tino, B. Si, and D. Ji. Neural Networks, (2021)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Fengzhen Tang

Fengzhen Zhang

Tang Tang

Junhua Tang

Fei Tang

Other publications of authors with the same name

Scan registration for underwater mechanical scanning imaging sonar using symmetrical Kullback-Leibler divergence.M. Jiang, S. Song, F. Tang, Y. Li, J. Liu, and X. Feng. J. Electronic Imaging, 28 (1): 013026 (2019)Nonstationary fuzzy neural network based on FCMnet clustering and a modified CG method with Armijo-type rule.B. Zhang, X. Gong, J. Wang, F. Tang, K. Zhang, and W. Wu. Inf. Sci., (2022)Generalized Learning Vector Quantization With Log-Euclidean Metric Learning on Symmetric Positive-Definite Manifold.F. Tang, P. Tino, and H. Yu. IEEE Trans. Cybern., 53 (8): 5178-5190 (2023)Vibration optimization of cantilevered bistable composite shells based on machine learning.C. Wu, R. Zhang, F. Tang, and M. Fan. Eng. Appl. Artif. Intell., 126 (Part D): 107158 (November 2023)Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices.F. Tang, H. Feng, P. Tiño, B. Si, and D. Ji. CoRR, (2021)Knowledge-based hybrid connectionist models for morphologic reasoning.K. He, W. Wang, G. Li, P. Yu, F. Tang, N. Xi, and L. Liu. Mach. Vis. Appl., 34 (2): 29 (March 2023)Prototype based linear sub-manifold learning.M. Fan, F. Tang, and X. Zhao. IJCNN, page 1-8. IEEE, (2023)Learning joint space-time-frequency features for EEG decoding on small labeled data.D. Zhao, F. Tang, B. Si, and X. Feng. Neural Networks, (2019)Generalized Learning Riemannian Space Quantization: A Case Study on Riemannian Manifold of SPD Matrices.F. Tang, M. Fan, and P. Tiño. IEEE Trans. Neural Networks Learn. Syst., 32 (1): 281-292 (2021)Dimension selection for EEG classification in the SPD Riemannian space based on PSO.Z. Zhang, Y. Guo, and F. Tang. Knowl. Based Syst., (November 2023)

BibSonomy

Disambiguation of "Tang, Fengzhen"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Probabilistic learning vector quantization on manifold of symmetric positive definite matrices.

Please choose a person to relate this publication to

Fengzhen Tang

Fengzhen Zhang

Tang Tang

Junhua Tang

Fei Tang

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Tang, Fengzhen"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Probabilistic learning vector quantization on manifold of symmetric positive definite matrices.

Please choose a person to relate this publication to

Fengzhen Tang

Fengzhen Zhang

Tang Tang

Junhua Tang

Fei Tang

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Probabilistic learning vector quantization on manifold of symmetric positive definite matrices.