5 citations · 5 across the 4 of their papers we have counts for
5 papers
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…
MBTI: A Multi-Branch Efficient Fine-Tuning Framework for Hyperspectral Image Classification with Foundation Models
Mingzhen Xu, Haonan Guo, Di Wang +9
Hyperspectral foundation models learn transferable spectral-spatial representations from large-scale unlabeled data. They provide an effective paradigm for adapting to downstream h…
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…
Remote Sensing ChatGPT: Solving Remote Sensing Tasks with ChatGPT and Visual Models
Haonan Guo, Xin Su, Chen Wu +3
Recently, the flourishing large language models(LLM), especially ChatGPT, have shown exceptional performance in language understanding, reasoning, and interaction, attracting users…
Exchange means change: an unsupervised single-temporal change detection framework based on intra- and inter-image patch exchange
Hongruixuan Chen, Jian Song, Chen Wu +2
Change detection (CD) is a critical task in studying the dynamics of ecosystems and human activities using multi-temporal remote sensing images. While deep learning has shown promi…