Abstract Unmanned Aerial Vehicle (UAV) remote sensing object recognition plays a vital
role in a variety of sectors including military, agriculture, forestry, and construction. Accurate …

The utilization of autonomous vehicles is experiencing a rapid proliferation in contemporary
society. Concurrently, with the relentless evolution of technology, the inexorable integration …

Multi-sensor fusion has been widely used by autonomous vehicles (AVs) to integrate the
perception results from different sensing modalities including LiDAR, camera and radar …

In autonomous driving, Frequency-Modulated Continuous-Wave (FMCW) radar has gained
widespread acceptance for target detection due to its resilience and dependability under …

Wireless sensing technology has become prevalent in healthcare, smart homes, and
autonomous driving due to its non-contact operation, penetration capabilities, and cost …

LiDAR (Light Detection and Ranging) has been widely used in autonomous driving to
perceive the surrounding environment of self-driving cars. Advanced LiDAR perception …

Autonomous mobile systems increasingly rely on deep neural networks for perception and
decision-making. While effective, these systems are vulnerable to adversarial machine …

Accurately localizing high-speed dynamic objects in 3D space with low latency is crucial for
various robotic applications. Current methods face challenges due to extended exposure …

Poisoning attacks are a primary threat to machine learning models, aiming to compromise
their performance and reliability by manipulating training datasets. This paper introduces a …