Artificial neural networks (ANNs) have emerged as an essential tool in machine learning,
achieving remarkable success across diverse domains, including image and speech …

Artificial Intelligence (Al) models are being produced and used to solve a variety of current
and future business and technical problems. Therefore, AI model engineering processes …

This article describes the artificial intelligence (AI) component of a drone for monitoring and
patrolling tasks associated with disaster relief missions in specific restricted disaster …

Ultralow-resolution infrared (IR) array sensors offer a low cost, energy efficient, and privacy-
preserving solution for people counting, with applications, such as occupancy monitoring …

Human Activity Recognition (HAR) based on inertial data is an increasingly diffused task on
embedded devices, from smartphones to ultra low-power sensors. Due to the high …

Accurate yet efficient Deep Neural Networks (DNNs) are in high demand, especially for
applications that require their execution on constrained edge devices. Finding such DNNs in …

With the increasing popularity of Internet of Things (IoT) devices, there is a growing need for
energy-efficient machine learning (ML) models that can run on constrained edge nodes …

Efficient target identification for bioactive compounds, including novel synthetic analogs, is
crucial for accelerating the drug discovery pipeline. However, the process of target …

The current trend of shifting computing from the cloud to the edge of the Internet of Things is
influencing deep learning applications. Moving intelligence closer to the point of need …

The knowledge of environmental depth is essential in multiple robotics and computer vision
tasks for both terrestrial and underwater scenarios. Moreover, the hardware on which this …