Over the past decades, a tremendous amount of research has been done on the use of
machine learning for speech processing applications, especially speech recognition …

Ultrasound (US) has become one of the most commonly performed imaging modalities in
clinical practice. It is a rapidly evolving technology with certain advantages and with unique …

Reservoir computing is a highly efficient network for processing temporal signals due to its
low training cost compared to standard recurrent neural networks, and generating rich …

The constantly increasing number of disclosed security vulnerabilities have become an
important concern in the software industry and in the field of cybersecurity, suggesting that …

Deep learning methods haverevolutionized speech recognition, image recognition, and
natural language processing since 2010. Each of these tasks involves a single modality in …

In the nervous system, dendrites, branches of neurons that transmit signals between
synapses and soma, play a critical role in processing functions, such as nonlinear …

In recent years, intelligent fault diagnosis algorithms using machine learning technique have
achieved much success. However, due to the fact that in real world industrial applications …

Deep neural networks (DNNs) are currently widely used for many artificial intelligence (AI)
applications including computer vision, speech recognition, and robotics. While DNNs …

Federated learning (FL) provides a communication-efficient approach to solve machine
learning problems concerning distributed data, without sending raw data to a central server …

Conversational systems have come a long way since their inception in the 1960s. After
decades of research and development, we have seen progress from Eliza and Parry in the …