This article aims to present the results of a bibliometric analysis of relevant literature and
discuss the main research streams related to the topic of risks in drone applications. The …

Smart cities are transforming by integrating artificial intelligence (AI) drones for various
applications, including traffic monitoring, public space management, and surveillance …

In the present technological world, surveillance cameras generate an immense amount of
video data from various sources, making its scrutiny tough for computer vision specialists. It …

The edge processing of deep neural networks (DNNs) is becoming increasingly important
due to its ability to extract valuable information directly at the data source to minimize latency …

This work discusses memory-immersed collaborative digitization among compute-in-
memory (CiM) arrays to minimize the area overheads of a conventional analog-to-digital …

Safety, low-cost, small size, and Artificial Intelli-gence (AI) capabilities of drones have led to
the proliferation of autonomous tiny Unmanned Aerial Vehicles (UAVs) in many applications …

This paper introduces a lightweight uncertainty estimator capable of predicting multimodal
(disjoint) uncertainty bounds by integrating conformal prediction with a deep-learning …

In various engineering fields, the fusion of infrared and visible images has important
applications. However, in the current process of fusing infrared and visible images, there are …

The increasing complexity of deep learning systems has pushed conventional computing
technologies to their limits. While the memristor is one of the prevailing technologies for …

Abstract In the'Beyond Moore's Law'era, with increasing edge intelligence, domain-specific
computing embracing unconventional approaches will become increasingly prevalent. At …