Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …

Electric vehicles are widely adopted globally as a sustainable mode of transportation. With
the increased availability of onboard computation and communication capabilities, vehicles …

Due to the workforce shortage caused by the declining birth rate and aging population,
robotics is one of the solutions to replace humans and overcome this urgent problem. This …

Due to highly constrained computing power and memory, deploying 3D lidar-based
detectors on edge devices equipped in autonomous vehicles and robots poses a crucial …

In reality, deploying the traditional object detection algorithm on mobile and embedded
devices is difficult due to the limited memory and computation resources. To solve this …

For many automotive functionalities in Advanced Driver Assist Systems (ADAS) and
Autonomous Driving (AD), target objects are detected using state-of-the-art Deep Neural …

The use of edge computing for 3D perception has garnered interest in intelligent
transportation systems (ITS) due to its potential to enhance Vehicle-to-Everything (V2X) …

In this paper, we propose a data-model-hardware tri-design framework for high-throughput,
low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video …

When machine learning (ML) models are supplied with data outside their training
distribution, they are more likely to make inaccurate predictions; in a cyber-physical system …

With advances in the Internet of Things, patients in intensive care units are constantly
monitored to expedite emergencies. Due to the COVID-19 pandemic, non-face-to-face …