An interpretable unsupervised capsule network via comprehensive contrastive learning and two-stage training

Limited attention has been given to unsupervised capsule networks (CapsNets) with contrastive learning due to the challenge of harmoniously learning interpretable primary and high-level capsules. To address this issue, we focus on three aspects: loss function, routing algorithm, and training strateg...

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Bibliographic Details

Published in:	Pattern recognition Vol. 158; p. 111059
Main Authors:	Zeng, Ru, Song, Yan, Zhong, Yanjiu
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.02.2025
Subjects:	Comprehensive contrastive loss Interpretability Primary capsules Routing algorithm Unsupervised capsule network Unsupervised capsule network Routing algorithm Comprehensive contrastive loss Interpretability Primary capsules
ISSN:	0031-3203
Online Access:	Get full text
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