1 citations · 1 across the 4 of their papers we have counts for
5 papers
Non-invasive Seizure Detection Using Wearable Wrist-worn Accelerometry and Deep Learning
Nilushika Udayangani Hewa Dehigahawattage, Kishor Nandakishor, Marimuthu Palaniswami
Seizure monitoring and detection are crucial for reducing the morbidity and mortality associated with seizures. Current epilepsy care, often involving expensive video-electroenceph…
Generative Diffusion Prior Distillation for Long-Context Knowledge Transfer
Nilushika Udayangani, Kishor Nandakishor, Marimuthu Palaniswami
While traditional time-series classifiers assume full sequences at inference, practical constraints (latency and cost) often limit inputs to partial prefixes. The absence of class-…
Task-Aligned Self-Supervised Learning for Medical Image Analysis: A Task-Oriented Review with Practical Design Guidelines
Chathura Wimalasiri, Yuchong Yao, Kishor Nandakishor +1
Self-supervised learning (SSL) is increasingly used in medical image analysis to reduce dependence on costly expert annotations by learning transferable representations from unlabe…
MemKD: Memory-Discrepancy Knowledge Distillation for Efficient Time Series Classification
Nilushika Udayangani, Kishor Nandakishor, Marimuthu Palaniswami
Deep learning models, particularly recurrent neural networks and their variants, such as long short-term memory, have significantly advanced time series data analysis. These models…
Learning to Reason: Temporal Saliency Distillation for Interpretable Knowledge Transfer
Nilushika Udayangani Hewa Dehigahawattage, Kishor Nandakishor, Marimuthu Palaniswami
Knowledge distillation has proven effective for model compression by transferring knowledge from a larger network called the teacher to a smaller network called the student. Curren…