Cross-Dataset Representation Learning for Unsupervised Deep Clustering in Human Activity Recognition

This study introduces a novel representation learning method to enhance unsupervised deep clustering in Human Activity Recognition (HAR). Traditional unsupervised deep clustering methods often struggle to extract effective feature representations from unlabeled data, failing to fully capture the tru...

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Bibliographic Details
Main Authors: Tomoya Takatsu, Tessai Hayama, Hu Cui
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10971938/
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