367 citations · 556 across the 8 of their papers we have counts for
8 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…
Classification of Short Segment Pediatric Heart Sounds Based on a Transformer-Based Convolutional Neural Network
Md Hassanuzzaman, Nurul Akhtar Hasan, Mohammad Abdullah Al Mamun +3
Congenital anomalies arising as a result of a defect in the structure of the heart and great vessels are known as congenital heart diseases or CHDs. A PCG can provide essential det…
CochCeps-Augment: A Novel Self-Supervised Contrastive Learning Using Cochlear Cepstrum-based Masking for Speech Emotion Recognition
Ioannis Ziogas, Hessa Alfalahi, Ahsan H. Khandoker +1
Self-supervised learning (SSL) for automated speech recognition in terms of its emotional content, can be heavily degraded by the presence noise, affecting the efficiency of modeli…
K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations
Cheul Young Park, Narae Cha, Soowon Kang +6
Recognizing emotions during social interactions has many potential applications with the popularization of low-cost mobile sensors, but a challenge remains with the lack of natural…
Progress in Brain Computer Interfaces: Challenges and Trends
Simanto Saha, Khondaker A. Mamun, Khawza Ahmed +5
Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by s…