A Multimodal Clustering Framework With Cross Reconstruction Autoencoders

A Multimodal Clustering Framework With Cross Reconstruction Autoencoders

Multimodal clustering algorithms partitions a multimodal dataset into disjoint clusters. Common feature extraction is a key part in multimodal clustering algorithms. Recently, deep neural networks shows high performance on latent feature extraction. However, existing works did not completely explore...

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Bibliographic Details
Main Authors: Qianli Zhao, Linlin Zong, Xianchao Zhang, Yuangang Li, Xiaorui Tang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Multimodal clustering
unsupervised deep learning
early fusion
Online Access:https://ieeexplore.ieee.org/document/9272372/

Internet

https://ieeexplore.ieee.org/document/9272372/

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