GeoSeC: Geometric-Semantic Collaborative Learning for Weakly Supervised Remote Sensing Image Segmentation
- DOI
- 10.1109/tip.2026.3734050
- Published
- 2026
- Container
- IEEE Transactions on Image Processing
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tip.2026.3734050,
title = {GeoSeC: Geometric-Semantic Collaborative Learning for Weakly Supervised Remote Sensing Image Segmentation},
author = {Xiangrong Zhang and Jianxun Lai and Guanchun Wang and Tianyang Zhang and Xu Tang},
year = {2026},
journal = {IEEE Transactions on Image Processing},
doi = {10.1109/tip.2026.3734050},
url = {https://doi.org/10.1109/tip.2026.3734050}
}RIS
TY - JOUR TI - GeoSeC: Geometric-Semantic Collaborative Learning for Weakly Supervised Remote Sensing Image Segmentation AU - Xiangrong Zhang AU - Jianxun Lai AU - Guanchun Wang AU - Tianyang Zhang AU - Xu Tang PY - 2026 JO - IEEE Transactions on Image Processing DO - 10.1109/tip.2026.3734050 UR - https://doi.org/10.1109/tip.2026.3734050 ER -
APA
Zhang, X., Lai, J., Wang, G., Zhang, T., & Tang, X. (2026). GeoSeC: Geometric-Semantic Collaborative Learning for Weakly Supervised Remote Sensing Image Segmentation. IEEE Transactions on Image Processing. https://doi.org/10.1109/tip.2026.3734050
Source records
- crossref · retrieved 2026-09-25T04:29:21.909Z