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Found 10 papers, 9 papers with code
Region-Disentangled Diffusion Model for High-Fidelity PPG-to-ECG Translation
In this work, we introduce Region-Disentangled Diffusion Model (RDDM), a novel diffusion model designed to capture the complex temporal dynamics of ECG.
Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts
Video self-supervised learning (VSSL) has made significant progress in recent years.
XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learning
First, masked data reconstruction is performed to learn modality-specific representations from audio and visual streams.
Ranked #1 on
Self-Supervised Action Recognition
on Kinetics-400
AVCAffe: A Large Scale Audio-Visual Dataset of Cognitive Load and Affect for Remote Work
We introduce AVCAffe, the first Audio-Visual dataset consisting of Cognitive load and Affect attributes.
Self-Supervised Audio-Visual Representation Learning with Relaxed Cross-Modal Synchronicity
We present CrissCross, a self-supervised framework for learning audio-visual representations.
Ranked #1 on
Audio Classification
on DCASE
Detection of Maternal and Fetal Stress from the Electrocardiogram with Self-Supervised Representation Learning
Our DL models accurately detect the chronic stress exposure group (AUROC=0. 982+/-0. 002), the individual psychological stress score (R2=0. 943+/-0. 009) and FSI at 34 weeks of gestation (R2=0. 946+/-0. 013), as well as the maternal hair cortisol at birth reflecting chronic stress exposure (0. 931+/-0. 006).
CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG
Electrocardiogram (ECG) is the electrical measurement of cardiac activity, whereas Photoplethysmogram (PPG) is the optical measurement of volumetric changes in blood circulation.
Self-supervised ECG Representation Learning for Emotion Recognition
Six different signal transformations are applied to the ECG signals, and transformation recognition is performed as pretext tasks.
Self-supervised Learning for ECG-based Emotion Recognition
Our proposed architecture consists of two main networks, a signal transformation recognition network and an emotion recognition network.
Classification of Cognitive Load and Expertise for Adaptive Simulation using Deep Multitask Learning
Simulations are a pedagogical means of enabling a risk-free way for healthcare practitioners to learn, maintain, or enhance their knowledge and skills.
