Realize Generative Yet Complete Latent Representation for Incomplete Multi-View Learning-Reference-Cited by-同舟云学术

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Realize Generative Yet Complete Latent Representation for Incomplete Multi-View Learning

Published:2024 Issue: Volume: Page:1-16
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Cai Hongmin¹^ORCID,Huang Weitian¹,Yang Sirui¹,Ding Siqi¹,Zhang Yue²^ORCID,Hu Bin³^ORCID,Zhang Fa³,Cheung Yiu-ming⁴^ORCID

Affiliation:

1. School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China

2. School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, Guangdong, China

3. School of Medical Technology, Beijing Institute of Technology, Beijing, China

4. Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/4359286/10373887.pdf?arnumber=10373887

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1. Cascaded Encoder-Decoder Reconstruction Network with Gated Mechanism for Multimodal Emotion Recognition under Missing Modalities;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

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