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Deep Recurrent Neural Networks for ECG Signal Denoising
[article]
2019
arXiv
pre-print
Electrocardiographic signal is a subject to multiple noises, caused by various factors. It is therefore a standard practice to denoise such signal before further analysis. With advances of new branch of machine learning, called deep learning, new methods are available that promises state-of-the-art performance for this task. We present a novel approach to denoise electrocardiographic signals with deep recurrent denoising neural networks. We utilize a transfer learning technique by pretraining
arXiv:1807.11551v3
fatcat:refjgwbxgfcxpcxv2gvycddgza