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Updated: Jan 13, 2026

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
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SGFNet:冗余减少的光谱空间融合网络用于高光谱图像分类

Boyu Wang1,2, Chi Cao1, Dexing Kong2

  • 1Faculty of Innovation and Engineering, Macau University of Science and Technology, Taipa 999078, Macau.

Entropy (Basel, Switzerland)
|October 28, 2025
PubMed
概括

通过减少光谱冗余和不确定性,SGFNet提高了高光谱图像分类 (HSIC). 这种光谱引导的融合网络提高了分析复杂的HSIC数据的准确性和效率.

关键词:
超光谱图像分类的分类方法减少了冗余性的裁员.具有光谱意识的过.频谱空间融合的频谱.

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