5 citations · 5 across the 2 of their papers we have counts for
4 papers
Self-Supervised Graph Representation Learning for In-The-Wild Wearable and Smartphone based Emotion Recognition
Ioannis N. Ziogas, Leontios J. Hadjileontiadis, Ahsan H. Khandoker +1
Wearable and smartphone-based emotion recognition (WER) remains a challenging setting in affective computing, due to the notorious difficulty and bias associated with in-the-wild l…
Automated detection of pediatric congenital heart disease from phonocardiograms using deep and handcrafted feature fusion
Abdul Jabbar, Ethan Grooby, Yang Yi Poh +5
Congenital heart disease (CHD) is the most common type of birth defect, impacting about 1% of live births worldwide. Echocardiography, the gold-standard diagnostic method, is costl…
Variational decomposition autoencoding improves disentanglement of latent representations
Ioannis Ziogas, Aamna Al Shehhi, Ahsan H. Khandoker +1
Understanding the structure of complex, nonstationary, high-dimensional time-evolving signals is a central challenge in scientific data analysis. In many domains, such as speech an…
Congenital Heart Disease Classification Using Phonocardiograms: A Scalable Screening Tool for Diverse Environments
Abdul Jabbar, Ethan Grooby, Jack Crozier +7
Congenital heart disease (CHD) is a critical condition that demands early detection, particularly in infancy and childhood. This study presents a deep learning model designed to de…