In data-intensive applications, it is advantageous to perform partial processing close to the
data, and communicate intermediate results to a central processor, instead of the data itself …

As the third-generation neural networks, Spiking Neural Networks (SNNs) have the potential
to replace ANNs in noisy input scenarios due to the advantages of low power consumption …

This chapter provides a nontechnical introduction to the machine learning (ML) discipline
aimed at a general audience with an affinity for biomedical applications. It familiarizes the …

This book provides an introduction into the field of digital medicine, its wide spectrum of
current clinical applications, and the future practice of medicine. With" digital health" and" …

The next ubiquitous computing platform, after personal computers and smartphones, is likely
one of the autonomous natures, such as drones, robots, and self-driving cars, which have …

ABSTRACT Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep
Learning (DL) is already present in many applications ranging from computer vision for …

Cyber-physical systems, built from the integration of cyber and physical components, are
being used in multiple domains ranging from manufacturing and healthcare to traffic control …

In this work, we explore theory and algorithms that improve the efficiency of various aspects
of machine learning systems. First, we investigate algorithmic principles that enable efficient …

As deep neural networks become more and more common in mission-critical applications,
such as smart medical care, drones, and autonomous driving, ensuring their reliable …

Intrusion target detection and recognition are of great significance to security protection of oil
and gas fields. An intrusion detection system is built with the integration of infrared image …