In the modern-day era of technology, a paradigm shift has been witnessed in the areas
involving applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep …

Autonomous vehicles (AVs) are the next-generation driver-less vehicular entities with
advanced technologies. Overtaking is an important and challenging maneuver that needs to …

In recent years, Deep Neural Network (DNN) has been increasingly adopted by a wide
range of time-critical applications running on edge platforms with heterogeneous …

Optimizing the quality of result (QoR) and the quality of service (QoS) of AI-empowered
autonomous systems simultaneously is very challenging. First, there are multiple input …

Heart disease, a global killer with many variations like arrhythmia and heart failure, remains
a major health concern. Traditional risk factors include age, cholesterol, diabetes, and blood …

The rapidly growing demands for powerful AI algorithms in many application domains have
motivated massive investment in both high-quality deep neural network (DNN) models and …

The convergence of edge computing systems with Field-Programmable Gate Array (FPGA)
technology has shown considerable promise in enhancing real-time applications across …

Recent advances in both lightweight deep learning algorithms and edge computing
increasingly enable multiple model inference tasks to be conducted concurrently on …

Environment perception technology is the most important part of driverless technology, and
driverless vehicles need to realize decision planning and control by virtue of perception …

In autonomous driving systems, high-speed and real-time image processing, along with
object recognition, are crucial technologies. This paper builds upon the research …