1 citations · 1 across the 5 of their papers we have counts for
5 papers
Quantifying Quanvolutional Neural Networks Robustness for Speech in Healthcare Applications
Ha Tran, Bipasha Kashyap, Pubudu N. Pathirana
Speech-based machine learning systems are sensitive to noise, complicating reliable deployment in emotion recognition and voice pathology detection. We evaluate the robustness of a…
Leveraging Vision Transformers for Enhanced Classification of Emotions using ECG Signals
Pubudu L. Indrasiri, Bipasha Kashyap, Pubudu N. Pathirana
Biomedical signals provide insights into various conditions affecting the human body. Beyond diagnostic capabilities, these signals offer a deeper understanding of how specific org…
Enhancing Federated Learning Through Secure Cluster-Weighted Client Aggregation
Kanishka Ranaweera, Azadeh Ghari Neiat, Xiao Liu +2
Federated learning (FL) has emerged as a promising paradigm in machine learning, enabling collaborative model training across decentralized devices without the need for raw data sh…
Quantum Approaches for Dysphonia Assessment in Small Speech Datasets
Ha Tran, Bipasha Kashyap, Pubudu N. Pathirana
Dysphonia, a prevalent medical condition, leads to voice loss, hoarseness, or speech interruptions. To assess it, researchers have been investigating various machine learning techn…
VR Based Emotion Recognition Using Deep Multimodal Fusion With Biosignals Across Multiple Anatomical Domains
Pubudu L. Indrasiri, Bipasha Kashyap, Chandima Kolambahewage +3
Emotion recognition is significantly enhanced by integrating multimodal biosignals and IMU data from multiple domains. In this paper, we introduce a novel multi-scale attention-bas…