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Preparation of Gynura bicolor DC samples for High-Resolution Tandem Mass Spectrometry
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基于对比学习的NIR光谱学和视觉线索的融合,用于分子歧视中国草本物种

Yu Yang1, Miao Li2, Xuehai Zhang3

  • 1Key Laboratory of Grain Information Processing and Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China; Henan Key Laboratory of Grain Photoelectric Detection and Control, Henan University of Technology, Zhengzhou 450001, China; College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China; Institute for Complexity Science, Henan University of Technology, Zhengzhou 450001, China.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
|December 11, 2025
PubMed
概括

准确识别中国药用草药至关重要. 一个新的跨模态神经框架 (CNRP) 集成了RGB成像和近红外 (NIR) 光谱,显著提高了细粒度草本分类的准确性.

关键词:
中国药用草药,中国药用草药.相反的学习学习.跨模式的学习学习.近红外光谱学近红外光谱学

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