348 citations · 1.1k across the 16 of their papers we have counts for
6 papers · 1 filter
SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification
Huy Phan, Kaare Mikkelsen, Oliver Y. Chén +3
Background: Black-box skepticism is one of the main hindrances impeding deep-learning-based automatic sleep scoring from being used in clinical environments. Methods: Towards inter…
Personalized Automatic Sleep Staging with Single-Night Data: a Pilot Study with KL-Divergence Regularization
Huy Phan, Kaare Mikkelsen, Oliver Y. Chén +4
Brain waves vary between people. An obvious way to improve automatic sleep staging for longitudinal sleep monitoring is personalization of algorithms based on individual characteri…
Improving GANs for Speech Enhancement
Huy Phan, Ian V. McLoughlin, Lam Pham +4
Generative adversarial networks (GAN) have recently been shown to be efficient for speech enhancement. However, most, if not all, existing speech enhancement GANs (SEGAN) make use…
Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning
Huy Phan, Oliver Y. Chén, Philipp Koch +4
Background: Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a…
Deep Transfer Learning for Single-Channel Automatic Sleep Staging with Channel Mismatch
Huy Phan, Oliver Y. Chén, Philipp Koch +2
Many sleep studies suffer from the problem of insufficient data to fully utilize deep neural networks as different labs use different recordings set ups, leading to the need of tra…
Unifying Isolated and Overlapping Audio Event Detection with Multi-Label Multi-Task Convolutional Recurrent Neural Networks
Huy Phan, Oliver Y. Chén, Philipp Koch +4
We propose a multi-label multi-task framework based on a convolutional recurrent neural network to unify detection of isolated and overlapping audio events. The framework leverages…