foundation models 1hyperspectral image classification 1low-rank adaptation 1multi-branch architecture 1spectral continuity 1
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cs.CV2026
PNEC-Mamba: Prototype-Guided Positive-Negative Evidence Calibration for Hyperspectral Image Classification
Mingzhen Xu, Can Xu, Di Wang +2
In real-world hyperspectral scenes, pixel representations are often ambiguous due to factors such as spectral similarity, mixed pixels, and local context interference, which may si…
cs.CV2026
MBTI: A Multi-Branch Efficient Fine-Tuning Framework for Hyperspectral Image Classification with Foundation Models
Mingzhen Xu, Haonan Guo, Di Wang +9
The paper introduces MBTI, a multi-branch fine‑tuning framework that adapts hyperspectral foundation models to classification tasks while preserving full‑band spectral information…
cs.CV2024
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Di Wang, Jing Zhang, Minqiang Xu +8
Foundation models have reshaped the landscape of Remote Sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervis…