[A lightweight classification network for single-lead atrial fibrillation based on depthwise separable convolution and attention mechanism].

This proposed method has a smaller complexity, achieves better classification performance, and has a better generalization ability for atrial fibrillation classification.

Authors

Chaomin Chen (ORCID: https://orcid.org/0000-0002-7661-1313)
Xin Zhang (ORCID: https://orcid.org/0000-0001-6822-3268)
Q. M. Jonathan Wu (ORCID: https://orcid.org/0000-0002-5208-7975)
Yong Hong
Mingjun Lin

Institutions

Southern Medical University (CN)

Publication Details

Journal: PubMed
Published: 2025-03-20
DOI: https://doi.org/10.12122/j.issn.1673-4254.2025.03.23
Primary Topic: Advanced Computing and Algorithms
Type: article

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article

[A lightweight classification network for single-lead atrial fibrillation based on depthwise separable convolution and attention mechanism].

Chaomin Chen, Xin Zhang, Q. M. Jonathan Wu, Yong Hong et al.

Mar 20, 2025

PubMed

Advanced Computing and Algorithms

article

[A lightweight classification network for single-lead atrial fibrillation based on depthwise separable convolution and attention mechanism].

Chaomin Chen, Xin Zhang, Q. M. Jonathan Wu, Yong Hong, Mingjun Lin

March 20, 2025article en

Abstract

This proposed method has a smaller complexity, achieves better classification performance, and has a better generalization ability for atrial fibrillation classification.

PubMedVol. 45(3)

Southern Medical University (CN)

Advanced Computing and Algorithms

DOI Source OpenAlex

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[A lightweight classification network for single-lead atrial fibrillation based on depthwise separable convolution and attention mechanism]. — Chaomin Chen, Xin Zhang, et al. · PubMed (2025) | TGRS Research Map | TGRS