Enhanced feature fusion through irrelevant redundancy elimination in intra-class and extra-class discriminative correlation analysis

Enhanced feature fusion through irrelevant redundancy elimination in intra-class and extra-class discriminative correlation analysis

Feature fusion aims to provide enhancements of data authenticity in both traditional and deep learning pattern analysis. Canonical Correlation Analysis (CCA) based feature fusion is a main technique for exploring the mutual relationships of multiple feature sets. In traditional CCA-based feature fus...

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書目詳細資料
Main Authors:	Wu, Zuobin, Mao, Kezhi, Ng, Gee-Wah
其他作者:	School of Electrical and Electronic Engineering
格式:	Article
語言:	English
出版:	2020
主題:	Engineering::Electrical and electronic engineering Feature Fusion Canonical Correlation Analysis
在線閱讀:	https://hdl.handle.net/10356/144648
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Nanyang Technological University
語言:	English

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