Deep convolutional neural networks (CNNs) have shown strong abilities in the application of artificial intelligence. However, due to their extensive amount of computation, traditional processors have low energy efficiency when executing CNN algorithm...
Synthetic aperture radar (SAR), which can generate images of regions or objects, is an important research area of radar. The chirp scaling algorithm (CSA) is a representative SAR imaging algorithm. The CSA has a simple structure comprising phase comp...
Internet of things (IoT) technology provides practical solutions for a wide range of applications, including but not limited to, smart homes, smart cities, intelligent grid, intelligent transportation, and healthcare. Security and privacy issues in I...
Security and privacy concerns pose significant obstacles to the widespread adoption of IoT technology. One potential solution to address these concerns is the implementation of cryptographic protocols on resource-constrained IoT edge nodes. However,...
This paper presents a polar-format algorithm (PFA)-based synthetic-aperture radar (SAR) processor that can be mounted on a small drone to support video SAR (ViSAR) imaging. For drone mounting, it requires miniaturization, low power consumption, and h...
The exponential emergence of Field-Programmable Gate Arrays (FPGAs) has accelerated research on hardware implementation of Deep Neural Networks (DNNs). Among all DNN processors, domain-specific architectures such as Google’s Tensor Processor Un...
Artificial Intelligence (AI) hardware accelerators have seen tremendous developments in recent years due to the rapid growth of AI in multiple fields. Many such accelerators comprise a Systolic Multiply–Accumulate Array (SMA) as its computation...
In the world of algorithm acceleration and the implementation of deep neural networks’ recall phase, OpenCL based solutions have a clear tendency to produce perfectly adapted kernels in graphic processor unit (GPU) architectures. However, they...
Transformer model is a type of deep learning model that has quickly become fundamental in natural language processing (NLP) and other machine learning tasks. Transformer hardware accelerators are usually designed for specific models, such as Bidirect...
Image analysis-based artificial intelligence (AI) models leveraging convolutional neural networks (CNN) take a significant role in evaluating the ripeness of strawberry, contributing to the maximization of productivity. However, the convolution, whic...
Over the past two decades, Long Short-Term Memory (LSTM) networks have been used to solve problems that require modeling of long sequence because they can selectively remember certain patterns over a long period, thus outperforming traditional feed-f...
In today’s TEST interconnected world, the security of 5G Medical IoT networks is of paramount concern. The increasing number of connected devices and the transmission of vast amounts of data necessitate robust measures to protect information in...
Artificial intelligence (AI) is one of the most promising technologies based on machine learning algorithms. In this paper, we propose a workflow for the implementation of deep neural networks. This workflow attempts to combine the flexibility of hig...
Noninvasive monitoring of blood flow in the carotid artery is important for evaluating not only cerebrovascular but also cardiovascular diseases. In this paper, a wireless neckband ultrasound Doppler system, in which two 2.5-MHz ultrasonic sensors ar...
Direction of Arrival (DoA) estimation is essential to adaptive beamforming widely used in many radar and wireless communication systems. Although many estimation algorithms have been investigated, most of them focus on the performance enhancement asp...
The rapid development of the Internet of Things (IoT) is transforming various economic and industrial sectors by embedding interconnected devices within their operational processes. However, security and privacy risks associated with these interconne...
Embedded systems increasingly require on-device deep learning, yet their processors must simultaneously handle real-time sensing, networking administration, and data control. Existing Field-Programmable Gate Array (FPGA) accelerators typically target...