SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction

1 code implementation • 8 Aug 2023 • Rahul G. S., Sriprabha Ramnarayanan, Mohammad Al Fahim, Keerthi Ram, Preejith S. P, Mohanasankar Sivaprakasam

The self-attention mechanism of the transformer enables transformers to capture long-range dependencies in the images, which might be desirable for accelerated MRI image reconstruction as the effect of undersampling is non-local in the image domain.

Computational Efficiency Image Reconstruction +2

Deep Network for Capacitive ECG Denoising

no code implementations • 29 Mar 2019 • Vignesh Ravichandran, Balamurali Murugesan, Sharath M. Shankaranarayana, Keerthi Ram, Preejith S. P, Jayaraj Joseph, Mohanasankar Sivaprakasam

We further evaluate the signal denoising using Mean Square Error(MSE) and Cross Correlation between model predictions and ground truth.

Denoising ECG Denoising +1

PPGnet: Deep Network for Device Independent Heart Rate Estimation from Photoplethysmogram

no code implementations • 21 Mar 2019 • Shyam A, Vignesh Ravichandran, Preejith S. P, Jayaraj Joseph, Mohanasankar Sivaprakasam

Traditional machine learning and deep learning approaches rely on tri-axial accelerometer data along with PPG to perform heart rate estimation.

Heart rate estimation Transfer Learning

RespNet: A deep learning model for extraction of respiration from photoplethysmogram

no code implementations • 12 Feb 2019 • Vignesh Ravichandran, Balamurali Murugesan, Vaishali Balakarthikeyan, Sharath M. Shankaranarayana, Keerthi Ram, Preejith S. P, Jayaraj Joseph, Mohanasankar Sivaprakasam

Recently, due to the widespread adoption of wearable smartwatches with in-built Photoplethysmogram (PPG) sensor, it is being considered as a viable candidate for continuous and unobtrusive respiration monitoring.