3 citations · 3 across the 4 of their papers we have counts for
5 papers
SNAP-V: A RISC-V SoC with Configurable Neuromorphic Acceleration for Small-Scale Spiking Neural Networks
Kanishka Gunawardana, Sanka Peeris, Kavishka Rambukwella +4
Spiking Neural Networks (SNNs) have gained significant attention in edge computing due to their low power consumption and computational efficiency. However, existing implementation…
Balancing Fidelity, Utility, and Privacy in Synthetic Cardiac MRI Generation: A Comparative Study
Madhura Edirisooriya, Dasuni Kawya, Ishan Kumarasinghe +5
Deep learning in cardiac MRI (CMR) is fundamentally constrained by both data scarcity and privacy regulations. This study systematically benchmarks three generative architectures:…
AICRN: Attention-Integrated Convolutional Residual Network for Interpretable Electrocardiogram Analysis
J. M. I. H. Jayakody, A. M. H. H. Alahakoon, C. R. M. Perera +4
The paradigm of electrocardiogram (ECG) analysis has evolved into real-time digital analysis, facilitated by artificial intelligence (AI) and machine learning (ML), which has impro…
Inductive transfer learning from regression to classification in ECG analysis
Ridma Jayasundara, Ishan Fernando, Adeepa Fernando +3
Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, accounting for over 30% of global deaths according to the World Health Organization (WHO). Importantly,…
AI-assisted radiographic analysis in detecting alveolar bone-loss severity and patterns
Chathura Wimalasiri, Piumal Rathnayake, Shamod Wijerathne +5
Periodontitis, a chronic inflammatory disease causing alveolar bone loss, significantly affects oral health and quality of life. Accurate assessment of bone loss severity and patte…