SpectralGPT: The first remote sensing foundation model customized for spectral data
Danfeng Hong, Bing Zhang, Xuyang Li, Yuxuan Li, Chen-Yu Li, Jing Yao, Naoto Yokoya, Hao Li 等 14 位
Chinese Academy of Sciences Aerospace Information Research Institute The University of Tokyo Technical University of Munich
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摘要与影响
SpectralGPT is the first purpose-built foundation model designed explicitly for spectral RS data. It considers unique characteristics of spectral data, i.e., spatial-spectral coupling and spectral sequentiality, in the MAE framework with a simple yet effective 3D GPT network. We will gradually release the trained models (SpectralGPT, SpectralGPT+), the new benchmark dataset (SegMunich) for the downstream task of semantic segmentation, original code, and implementation instructions.
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学术脉络
学科主题
计算机 / AIAdvanced Computational Techniques and Applications
Remote-Sensing Image Classification · Remote Sensing and Land Use
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