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Deep multi-view learning methods: a review: A review
Xiaoqiang Yan
, Shizhe Hu
, Yiqiao Mao
, Yangdong Ye
*
, Hui Yu
*
Corresponding author for this work
University of Portsmouth
Centre for Creative and Immersive XR
Zhengzhou University
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Computer Science
Multiview Learning Method
100%
Multi-View Learning
100%
Deep Learning Method
33%
Traditional Method
16%
Research Direction
16%
Correlation Analysis
16%
Deep Learning Model
16%
Artificial Intelligence
16%
Machine Learning
16%
Learning System
16%
Learning Mechanism
16%
Computer Vision
16%
Conventional Neural Network
16%
Performance Comparison
16%
Matrix Factorization
16%
INIS
reviews
100%
learning
100%
information
15%
performance
15%
comparative evaluations
7%
applications
7%
correlations
7%
datasets
7%
increasing
7%
neural networks
7%
machine learning
7%
matrices
7%
vision
7%
computers
7%
artificial intelligence
7%
factorization
7%
Chemical Engineering
Deep Learning Method
100%
Artificial Intelligence
33%
Learning System
33%
Neural Network
33%
Correlation Analysis
33%