Learning forward-compatible and domain-invariant representations for cross-domain few-shot class-incremental learning.
- DOI
- 10.1016/j.neunet.2026.109070
- Published
- 2026 Oct
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109070,
title = {Learning forward-compatible and domain-invariant representations for cross-domain few-shot class-incremental learning.},
author = {Shi W and Yan X and Yuan J and Lu H and Feng S},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.109070},
url = {https://doi.org/10.1016/j.neunet.2026.109070}
}RIS
TY - JOUR TI - Learning forward-compatible and domain-invariant representations for cross-domain few-shot class-incremental learning. AU - Shi W AU - Yan X AU - Yuan J AU - Lu H AU - Feng S PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.109070 UR - https://doi.org/10.1016/j.neunet.2026.109070 ER -
APA
W, S., X, Y., J, Y., H, L., & S, F. (2026). Learning forward-compatible and domain-invariant representations for cross-domain few-shot class-incremental learning.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109070
Source records
- pubmed · retrieved 2026-09-25T22:27:19.839Z
- europe-pmc · retrieved 2026-09-25T22:27:19.852Z