Arrhythmia Classifier Using Convolutional Neural Network with Adaptive Loss-aware Multi-bit Networks Quantization-Reference-Cited by-同舟云学术

Arrhythmia Classifier Using Convolutional Neural Network with Adaptive Loss-aware Multi-bit Networks Quantization

Published:2021-11 Issue: Volume: Page:
ISSN:
Container-title:2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE)
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Author:

Sun Hanshi¹,Wang Ao¹,Pu Ninghao¹,Li Zhiqing¹,Huang Junguang¹,Liu Hao²,Qi Zhi²

Affiliation:

1. School of Electronic Science and Engineering Southeast University,Nanjing,Jiangsu,China

2. Southeast University,National ASIC System Engineering Research Center,Nanjing,Jiangsu,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9797458/9797460/09797527.pdf?arnumber=9797527

Reference25 articles.

1. Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks

2. Towards interpretable and maintainable supervised learning using shapley values in arrhythmia;krishnakumar;Proceedings of the 30th Annual International Conference on Computer Science and Software Engineering ser CASCON '20,2020

3. Arrhythmia Classifier Using a Layer-wise Quantized Convolutional Neural Network for Resource-Constrained Devices

4. Application of convolutional neural network in automatic classification of arrhythmia

5. Heartbeat Classification Using Feature Selection Driven by Database Generalization Criteria

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