Which Augmentation Should I Use? An Empirical Investigation of Augmentations for Self-Supervised Phonocardiogram Representation Learning

1 December 2023

Papers citing "Which Augmentation Should I Use? An Empirical Investigation of Augmentations for Self-Supervised Phonocardiogram Representation Learning"

4 / 4 papers shown

Title
Beyond Heart Murmur Detection: Automatic Murmur Grading from Phonocardiogram A. Elola E. Aramendi J. Oliveira F. Renna M. Coimbra Matthew A. Reyna Reza Sameni Gari D. Clifford Ali Bahrami Rad 19 11 0 27 Sep 2022
Intra-Inter Subject Self-supervised Learning for Multivariate Cardiac Signals Xiang Lan Dianwen Ng linda Qiao Mengling Feng OOD 43 51 0 18 Sep 2021
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning Yifan Zhang Bryan Hooi Dapeng Hu Jian Liang Jiashi Feng 64 64 0 12 Feb 2021
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data Demetres Kostas Stephane Aroca-Ouellette Frank Rudzicz SSL 41 198 0 28 Jan 2021