LANet: A Lightweight and Accurate Balanced Network Based on State Space Models for Real-Time Semantic Segmentation.
- DOI
- 10.1109/tnnls.2026.3708426
- Published
- 2026-07-07
- Container
- IEEE Trans Neural Netw Learn Syst
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2026.3708426,
title = {LANet: A Lightweight and Accurate Balanced Network Based on State Space Models for Real-Time Semantic Segmentation.},
author = {Zhuang M and Liu S and Wang G and Wang Y and Wang H.},
year = {2026},
journal = {IEEE Trans Neural Netw Learn Syst},
doi = {10.1109/tnnls.2026.3708426},
url = {https://doi.org/10.1109/tnnls.2026.3708426}
}RIS
TY - JOUR TI - LANet: A Lightweight and Accurate Balanced Network Based on State Space Models for Real-Time Semantic Segmentation. AU - Zhuang M AU - Liu S AU - Wang G AU - Wang Y AU - Wang H. PY - 2026 JO - IEEE Trans Neural Netw Learn Syst DO - 10.1109/tnnls.2026.3708426 UR - https://doi.org/10.1109/tnnls.2026.3708426 ER -
APA
M, Z., S, L., G, W., Y, W., & H., W. (2026). LANet: A Lightweight and Accurate Balanced Network Based on State Space Models for Real-Time Semantic Segmentation.. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/tnnls.2026.3708426
Source records
- europe-pmc · retrieved 2026-09-25T08:51:00.693Z