HIGHLIGHTS
- who: Fanchen Zheng from the College of Science, China Agricultural University, Beijing, China have published the paper: Facial Expression Recognition Based on LDA Feature Space Optimization, in the Journal: Computational Intelligence and Neuroscience of 29/08/2022
- what: The authors compare the effects of PCA and LDA feature dimensionality reduction methods on facial expression recognition. The main reason is that LDA feature dimensionality reduction increases the correlation between features and categories; that is, the class spacing is maximized while the intraclass dispersion is minimized, so that the subsequent model can better learn the interclass differences . . .
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