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Found 7 papers, 4 papers with code
RPnet: A Deep Learning approach for robust R Peak detection in noisy ECG
Furthermore, the model was also evaluated on three other databases.
KD-MRI: A knowledge distillation framework for image reconstruction and image restoration in MRI workflow
In our work, we propose a knowledge distillation (KD) framework for the image to image problems in the MRI workflow in order to develop compact, low-parameter models without a significant drop in performance.
A Deep Knowledge Distillation framework for EEG assisted enhancement of single-lead ECG based sleep staging
This demonstrates the viability of KD for performance improvement of single-channel ECG based sleep staging in 4-class(W-L-D-R) and 3-class(W-N-R) classification.
Multitask Network for Respiration Rate Estimation -- A Practical Perspective
The multitasking network consists of a combination of Encoder-Decoder and Encoder-IncResNet, to fetch the average respiration rate and the respiration signal.
Interpreting Deep Neural Networks for Single-Lead ECG Arrhythmia Classification
However, these traditional methods require expert knowledge and are unable to model a wide range of arrhythmia.
Robust Modelling of Reflectance Pulse Oximetry for SpO$_2$ Estimation
Recently, a Machine Learning (ML) method was used to model reflectance waveforms onto SpO$_2$ obtained from transmittance waveforms.
A deep cascade of ensemble of dual domain networks with gradient-based T1 assistance and perceptual refinement for fast MRI reconstruction
In our work, we develop deep networks to further improve the quantitative and the perceptual quality of reconstruction.
