A Dynamic Adaptive Framework for Remote Sensing Imagery Superpixel Segmentation and Classification via Dual-Branch Feature Learning
- DOI
- 10.1109/jstars.2025.3585544
- Published
- 2025
- Container
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1109/jstars.2025.3585544,
title = {A Dynamic Adaptive Framework for Remote Sensing Imagery Superpixel Segmentation and Classification via Dual-Branch Feature Learning},
author = {Wangtun Yang and Yang Zhang and Heng Zhang and Liangzhi Li},
year = {2025},
journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
doi = {10.1109/jstars.2025.3585544},
url = {https://doi.org/10.1109/jstars.2025.3585544}
}RIS
TY - JOUR TI - A Dynamic Adaptive Framework for Remote Sensing Imagery Superpixel Segmentation and Classification via Dual-Branch Feature Learning AU - Wangtun Yang AU - Yang Zhang AU - Heng Zhang AU - Liangzhi Li PY - 2025 JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing DO - 10.1109/jstars.2025.3585544 UR - https://doi.org/10.1109/jstars.2025.3585544 ER -
APA
Yang, W., Zhang, Y., Zhang, H., & Li, L. (2025). A Dynamic Adaptive Framework for Remote Sensing Imagery Superpixel Segmentation and Classification via Dual-Branch Feature Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/jstars.2025.3585544
Source records
- doaj · retrieved 2026-09-27T09:29:52.132Z