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Deep neural network-based generalized sidelobe canceller for dual-channel far-field speech recognition.

Neural networks : the official journal of the International Neural Network Society
The traditional generalized sidelobe canceller (GSC) is a common speech enhancement front end to improve the noise robustness of automatic speech recognition (ASR) systems in the far-field cases. However, the traditional GSC is optimized based on the...

Deep ANC: A deep learning approach to active noise control.

Neural networks : the official journal of the International Neural Network Society
Traditional active noise control (ANC) methods are based on adaptive signal processing with the least mean square algorithm as the foundation. They are linear systems and do not perform satisfactorily in the presence of nonlinear distortions. In this...

Speaker recognition based on deep learning: An overview.

Neural networks : the official journal of the International Neural Network Society
Speaker recognition is a task of identifying persons from their voices. Recently, deep learning has dramatically revolutionized speaker recognition. However, there is lack of comprehensive reviews on the exciting progress. In this paper, we review se...

Introducing Swish and Parallelized Blind Removal Improves the Performance of a Convolutional Neural Network in Denoising MR Images.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: To improve the performance of a denoising convolutional neural network (DnCNN) and to make it applicable to images with inhomogeneous noise, a refinement involving an activation function (AF) and an application of the refined method for inho...

Preictal state detection using prodromal symptoms: A machine learning approach.

Epilepsia
A reliable identification of a high-risk state for upcoming seizures may allow for preemptive treatment and improve the quality of patients' lives. We evaluated the ability of prodromal symptoms to predict preictal states using a machine learning (ML...

Inter-floor noise classification using convolutional neural network.

PloS one
In apartment houses, noise between floors can disturb pleasant living environments and cause disputes between neighbors. As a means of resolving disputes caused by inter-floor noise, noises are recorded for 24 hours in a household to verify whether t...

Addressing Noise and Skewness in Interpretable Health-Condition Assessment by Learning Model Confidence.

Sensors (Basel, Switzerland)
Assessing the health condition has a wide range of applications in healthcare, military, aerospace, and industrial fields. Nevertheless, traditional feature-engineered techniques involve manual feature extraction, which are too cumbersome to adapt to...

Modelling the effects of transcranial alternating current stimulation on the neural encoding of speech in noise.

NeuroImage
Transcranial alternating current stimulation (tACS) can non-invasively modulate neuronal activity in the cerebral cortex, in particular at the frequency of the applied stimulation. Such modulation can matter for speech processing, since the latter in...

Prospective Validation of Vesical Imaging-Reporting and Data System Using a Next-Generation Magnetic Resonance Imaging Scanner-Is Denoising Deep Learning Reconstruction Useful?

The Journal of urology
PURPOSE: The Vesical Imaging Reporting and Data System (VI-RADS) was launched in 2018 to standardize reporting of magnetic resonance imaging for bladder cancer. This study aimed to prospectively validate VI-RADS using a next-generation magnetic reson...

The Silent Operation Theatre Optimisation System (SOTOS) to reduce noise pollution during da Vinci robot-assisted laparoscopic radical prostatectomy.

Journal of robotic surgery
To reduce noise pollution and consequently stress during robot-assisted laparoscopic radical prostatectomy (RALP) the aim of our study was to evaluate the silent operation theatre optimisation system (SOTOS) in its effectiveness. In the operating roo...