Essential Number of Principal Components and Nearly Training-Free Model for Spectral Analysis
Learning-enabled spectroscopic analysis, promising for automated real-time analysis of chemicals, is facing several challenges. First, a typical machine learning model requires a large number of training samples that physical systems can not provide. Second, it requires the testing samples to be in...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 12 vom: 01. Nov., Seite 9714-9726
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| 1. Verfasser: |
Bie, Yifeng
(VerfasserIn) |
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| Weitere Verfasser: |
You, Shuai,
Li, Xinrui,
Zhang, Xuekui,
Lu, Tao |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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