Abstract: This paper proposes a novel Globality Locality Preserving Canonical Correlation Analysis (GLPCCA) for multiview learning.
ABSTRACT. This paper proposes a novel Globality Locality Preserving. Canonical Correlation Analysis (GLPCCA) for multiview learning.
Human action recognition by fusing deep features with Globality Locality Preserving Canonical Correlation Analysis. El Din El Madany, N., He, Y., & Guan, L.
In this paper, we study the problem of human action recognition, in which each action is captured by multiple sensors and represented by multisets.
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Paper Detail ; Paper Title: HUMAN ACTION RECOGNITION BY FUSING DEEP FEATURES WITH GLOBALITY LOCALITY PRESERVING CANONICAL CORRELATION ANALYSIS ; Authors: Nour El ...
A new human action recognition framework employing the proposed BGLPCCA or MGLP CCA to learn the shared subspace from multiple sets of features including ...
Human action recognition by fusing deep features with Globality Locality Preserving Canonical Correlation Analysis · Nour El-Din El-Madany, Yifeng He, Ling ...
2016. Human action recognition by fusing deep features with globality locality preserving canonical correlation analysis. NED El Madany, Y He, L Guan. 2017 ...
CCECE 2022; Readers: Everyone. Human action recognition by fusing deep features with Globality Locality Preserving Canonical Correlation Analysis · pdf icon ...
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Ling Guan · View · Human action recognition by fusing deep features with Globality Locality Preserving Canonical Correlation Analysis. Conference Paper. Sep ...