2021
DOI: 10.1002/cpe.6660
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Multi‐label enhancement manifold learning algorithm for vehicle video

Abstract: In this article, we propose a new multi‐label enhancement manifold learning algorithm to solve the vehicle video classification problem. Predicting multiple objects in a traffic video image is a challenging problem. Traditional multi‐label classification methods can solve the problem of simultaneous detection of multiple labels, but cannot handle high‐dimensional streaming video data. Our idea is to use label distribution learning (LDL) to enrich the label space and improve label recognition in the original la… Show more

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Cited by 3 publications
(1 citation statement)
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“…Among the existing dimensionality reduction methods (Zhang et al, 2021;Tan et al, 2021), independent component analysis and principal component analysis are very effective for processing data sets with linear structure, and the results of wavelet, Fourier transform and Had2mard transform for image processing are also satisfactory. The independent component analysis assumes that the data set is formed by the superposition of signals generated by multiple internal sources, and the linear structure of the data is obtained by minimizing mutual information according to information theory.…”
mentioning
confidence: 99%
“…Among the existing dimensionality reduction methods (Zhang et al, 2021;Tan et al, 2021), independent component analysis and principal component analysis are very effective for processing data sets with linear structure, and the results of wavelet, Fourier transform and Had2mard transform for image processing are also satisfactory. The independent component analysis assumes that the data set is formed by the superposition of signals generated by multiple internal sources, and the linear structure of the data is obtained by minimizing mutual information according to information theory.…”
mentioning
confidence: 99%