Cross-Domain Pattern Classification With Distribution Adaptation Based on Evidence Theory
- DOI
- 10.1109/tcyb.2021.3133890
- Published
- 2023-02
- Container
- IEEE Transactions on Cybernetics
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tcyb.2021.3133890,
title = {Cross-Domain Pattern Classification With Distribution Adaptation Based on Evidence Theory},
author = {Lin-Qing Huang and Zhun-Ga Liu and Jean Dezert},
year = {2023},
journal = {IEEE Transactions on Cybernetics},
doi = {10.1109/tcyb.2021.3133890},
url = {https://doi.org/10.1109/tcyb.2021.3133890}
}RIS
TY - JOUR TI - Cross-Domain Pattern Classification With Distribution Adaptation Based on Evidence Theory AU - Lin-Qing Huang AU - Zhun-Ga Liu AU - Jean Dezert PY - 2023 JO - IEEE Transactions on Cybernetics DO - 10.1109/tcyb.2021.3133890 UR - https://doi.org/10.1109/tcyb.2021.3133890 ER -
APA
Huang, L., Liu, Z., & Dezert, J. (2023). Cross-Domain Pattern Classification With Distribution Adaptation Based on Evidence Theory. IEEE Transactions on Cybernetics. https://doi.org/10.1109/tcyb.2021.3133890
Source records
- crossref · retrieved 2026-11-10T12:14:25.514Z