Multi-patch embedding canonical correlation analysis for multi-view feature learning-Reference-Cited by-同舟云学术

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Multi-patch embedding canonical correlation analysis for multi-view feature learning

Published:2016-11 Issue: Volume:41 Page:47-57
ISSN:1047-3203
Container-title:Journal of Visual Communication and Image Representation
language:en
Short-container-title:Journal of Visual Communication and Image Representation

Author:

Su Shuzhi,Ge Hongwei,Yuan Yun-Hao

Funder

Graduate Innovation Project of Jiangsu Province

111 Project

Jiangsu Higher Education Institutions

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Media Technology,Signal Processing

Reference35 articles.

1. Dynamic probabilistic CCA for analysis of affective behavior and fusion of continuous annotations;Nicolaou;IEEE Trans. Pattern Anal. Mach. Intell.,2014

2. Fractional-order embedding canonical correlation analysis and its applications to multi-view dimensionality reduction and recognition;Yuan;Pattern Recogn.,2014

3. Relations between two sets of variates;Hotelling;Biometrika,1936

4. A new method of feature fusion and its application in image recognition;Sun;Pattern Recogn.,2005

5. Kernel canonical correlation analysis for assessing gene–gene interactions and application to ovarian cancer;Larson;Eur. J. Hum. Genet.,2014

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1. Cross-view learning with scatters and manifold exploitation in geodesic space;Electronic Research Archive;2023

2. Neighbor-consistent multi-modal canonical correlations for feature fusion;Infrared Physics & Technology;2022-06

3. Clustering adaptive canonical correlations for high-dimensional multi-modal data;Journal of Visual Communication and Image Representation;2020-08

4. A Convex Discriminant Semantic Correlation Analysis for Cross-View Recognition;IEEE Transactions on Cybernetics;2020

5. Multi-graph embedding discriminative correlation feature learning for image recognition;Signal Processing: Image Communication;2018-02

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