Automatic Cardiac Arrhythmia Classification Using Residual Network Combined With Long Short-Term Memory-Reference-Cited by-同舟云学术

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Automatic Cardiac Arrhythmia Classification Using Residual Network Combined With Long Short-Term Memory

Published:2022 Issue: Volume:71 Page:1-17
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Kim Yun Kwan¹^ORCID,Lee Minji¹^ORCID,Song Hee Seok²^ORCID,Lee Seong-Whan³^ORCID

Affiliation:

1. Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea

2. Technology Development, Seers Technology Company Ltd., Seongnam-si, Republic of Korea

3. Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea

Funder

Korean Medical Device Development

Korean Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09794445.pdf?arnumber=9794445

Reference95 articles.

1. Deep learning with convolutional neural networks for EEG decoding and visualization

2. Few-Shot Learning With Geometric Constraints

3. Self-augmentation: Generalizing deep networks to unseen classes for few-shot learning

4. Few-Shot Object Detection on Remote Sensing Images via Shared Attention Module and Balanced Fine-Tuning Strategy

5. ECG-based heartbeat classification for arrhythmia detection: A survey

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